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The recent advancement in Unmanned Aerial Vehicles (UAVs) in terms of manufacturing processes, and communication and networking technology has led to a rise in their usage in civilian and commercial applications. The regulations of the Federal Aviation Administration (FAA) in the US had earlier limited the usage of UAVs to military applications. However more recently, the FAA has outlined new enforcement that will also expand the usage of UAVs in civilian and commercial applications. Due to being deployed in open atmosphere, UAVs are vulnerable to being lost, destroyed or physically hijacked. With the UAV technology becoming ubiquitous, various issues in UAV networks such as intra-UAV communication, UAV security, air data security, data storage and management, etc. need to be addressed. Blockchain being a distributed ledger protects the shared data using cryptography techniques such as hash functions and public key encryption. It can also be used for assuring the truthfulness of the information stored and for improving the security and transparency of the UAVs. In this paper, we review various applications of blockchain in UAV networks such as network security, decentralized storage, inventory management, surveillance, etc., and discuss some broader perspectives in this regard. We also discuss various challenges to be addressed in the integration of blockchain and UAVs and suggest some future research directions. Index Terms-Unmanned Aerial Vehicle (UAV) network, security and privacy, blockchain technology, Internet of Things (IoT).
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Applications of Blockchain in Unmanned Aerial Vehicles: A Review
Tejasvi Alladi, Vinay Chamola, Nishad Sahu, and Mohsen Guizani
Abstract—The recent advancement in Unmanned Aerial Vehi-
cles (UAVs) in terms of manufacturing processes, and communi-
cation and networking technology has led to a rise in their usage
in civilian and commercial applications. The regulations of the
Federal Aviation Administration (FAA) in the US had earlier
limited the usage of UAVs to military applications. However
more recently, the FAA has outlined new enforcement that will
also expand the usage of UAVs in civilian and commercial
applications. Due to being deployed in open atmosphere, UAVs
are vulnerable to being lost, destroyed or physically hijacked.
With the UAV technology becoming ubiquitous, various issues in
UAV networks such as intra-UAV communication, UAV security,
air data security, data storage and management, etc. need to
be addressed. Blockchain being a distributed ledger protects the
shared data using cryptography techniques such as hash func-
tions and public key encryption. It can also be used for assuring
the truthfulness of the information stored and for improving the
security and transparency of the UAVs. In this paper, we review
various applications of blockchain in UAV networks such as
network security, decentralized storage, inventory management,
surveillance, etc., and discuss some broader perspectives in this
regard. We also discuss various challenges to be addressed in
the integration of blockchain and UAVs and suggest some future
research directions.
Index Terms—Unmanned Aerial Vehicle (UAV) network, secu-
rity and privacy, blockchain technology, Internet of Things (IoT).
Unmanned Aerial Vehicles (UAVs) are a class of robotic
vehicles that can carry payloads and execute flying missions
guided either by remote control stations or in an autonomous
way. UAVs are very mobile, which enables them to function
even in remote areas where there is no physical or techno-
logical infrastructure. Originally UAVs were used only for
military applications. However, with their increasing popu-
larity, technological advancements and awareness among the
people in industry and research, their applications are no
longer limited to military applications [1]. As highlighted in
Fig. 1, some of the different applications where UAVs are
used today are [2]- rescue operations [3], saving lives [4],
agriculture and farming [5], building structures [6], pipeline
inspections [7], delivering goods and medical supplies [8],
video capturing and filming [9] and surveying [10]. Apart
from these, there are many more applications such as inventory
management, surveillance monitoring activities and providing
relayed telecommunication services where UAVs are being
used. Thus they have a huge scope for applications in a
wide variety of fields in both civil and military domains. A
Tejasvi Alladi, Vinay Chamola and Nishad Sahu are with the De-
partment of Electrical and Electronics Engineering, BITS-Pilani, Pi-
lani Campus, India 333031 (e-mail:;;
Mohsen Guizani is with the Department of Computer Science, Qatar
University, Qatar (e-mail: ).
Deliver goods and
medical supplies
Filming Rescuing
Building structures Pipe inspections
Save lives
Fig. 1: Application of UAVs in various fields as discussed in
Non-Governmental Organisation (NGO) in Japan employed
UAVs to inspect unlicensed Japanese whaling that was going
on in the southern hemisphere [11]. Also, after the devas-
tating Japanese earthquake and tsunami which occurred in
2011, three different types of UAVs were deployed during
the emergency operations to closely monitor the Fukushima
nuclear power plant. The inputs received from these UAVs
were crucial for carrying out the emergency operations [12].
Such applications have encouraged the research and scientific
communities to actively explore the domain of UAVs and how
to enhance their operational capabilities.
UAVs are associated with solving new problems and are
involved in a variety of new activities in the technological
domain leading to the growth of the UAV market. They are
also being actively explored for acting as base stations in
communication networks [13]–[17]. A lot of agencies are
involved in developing UAVs to bring down the cost associated
with the connected services. There are also many studies which
are coming up with improved authentication protocols for UAV
and vehicle to vehicle communications such as [18]–[21]. This
will increase the efficiency of UAV communications in the
future. UAVs also offer a lot of flexibility, are easy to deploy,
can be customized to take high-resolution images even while
performing difficult tasks. They can also operate in remote
locations that are otherwise physically inaccessible such as
deep forest areas. Very few countries have enacted laws for
the protection of privacy and data in UAV. Since most of the
UAVs are typically deployed in the security and military areas,
the issues that are generally faced are related to security, safety,
privacy, and ethics [22].
This increase in the number of UAVs poses new challenges
such as rising air traffic, laying optimal paths, generating
flight plans, dealing with emergencies such as collisions and
managing UAV swarms, and cyber-physical attacks on UAVs.
Research has shown that these challenges can be mitigated
with the help of powerful tools such as blockchain [23]–
[25]. Blockchain is seen as a way to empower the UAVs
and make them safer, more accurate and easy to control.
Most of the UAV applications involve coordination with other
robots or UAVs for operational purposes. This makes them
suitable candidates for blockchain incorporation. A newer
infrastructure to provide adaptability, scalability and the ability
to deliver efficient and fast services would be required to cater
to the upcoming needs. To deal with the above-mentioned
issues, blockchain technology is being looked upon as a way
to deliver a framework that can be put to use in the commercial
UAV industry.
The major contributions of this work are summarized as
To the best of our knowledge, this is the first study
summarizing the various applications of blockchain tech-
nology in UAV systems.
We divide the study into different application scenarios
where UAV systems are used and discuss how blockchain
can enhance their utility in each scenario. We also discuss
the challenges pertaining to each scenario.
This survey provides an in-depth study of how certain
blockchain features can help overcome drawbacks of
UAV systems and discusses application-specific examples
for each of them.
The survey also gives a broader outlook to the readers,
on how the combination of blockchain and UAV tech-
nology can influence many other emerging technologies
and how those emerging technologies can influence the
development of blockchain-based UAV systems.
Based on our comprehensive survey we provide potential
research directions that can be beneficial for the devel-
opment of blockchain-based UAV systems.
A. Paper organization
The organization of this paper is as follows. We give a
brief overview of the fundamentals of UAV and blockchain
technologies, and the scope of their integration which is the
topic of this paper, in Section II. From section III to VIII, we
discuss various applications of blockchain in UAV. In section
IX, we give the broader perspectives on the applicability of
blockchain technology in UAVs and discuss some of the other
interesting applications. To provide the readers with an overall
picture of the research in blockchain-based UAV networks and
predict possible research opportunities, we discuss the overall
challenges involved and suggest future research directions in
the implementation of blockchain-based UAV networks in
Section X. We finally end the paper with Section XI giving a
conclusion of the study.
In this section, we briefly discuss various fundamentals of
UAVs and blockchain technology. Subsequently, we discuss
how combining these technologies can open up a lot of
exciting possibilities for the future.
A. Unmanned Aerial Vehicles
UAVs have both electronic components and mechanical
power components, with their operations being quite complex.
Generally, there is an operating system on-board these devices
on which the software for the UAV runs [26]. An overall
picture of the UAV technology in terms of their classifications
based on different parameters, regulations regarding their op-
erations and different application scenarios is presented below.
1) UAV classifications: UAVs can be classified based on
various parameters such as flying mechanism, weight, flying
altitude, and wing type. Based on the flying mechanism, UAVs
can be categorized as follows [27].
i. Multi-rotor or rotary-wing UAVs: Such UAVs are capable
of taking off and landing vertically and can also hover
over a particular location. However, such UAVs have
relatively lesser mobility compared to other UAV types.
Also, these UAVs consume more power since they have
to act opposite to the gravitational force.
ii. Fixed wing UAVs: Such UAV types can travel via gliding
in the atmosphere like commercial airplanes and can also
carry heavy payloads. Such a flying style enables them
to travel faster compared to other UAV types but at the
same time, this makes it mandatory for them to take-off
and land on a runway. Also, they are incapable of hovering
over a particular area like the multi-rotor UAVs and are
generally costlier compared to multi-rotor UAVs.
iii. Hybrid fixed/rotary-wing UAVs: This type of UAV is a
compromise between the above two mechanisms and can
switch between the two. An example of this is the Parrot
type which can do a vertical take-off, glide through its
path and then again switch to hovering using its rotors
Out of these, the UAV types which can hover over a particular
area operate easily in multi-UAV swarm systems for appli-
cations such as surveillance. Such applications are suitable
for incorporating blockchain-based solutions to ensure secure
communication and trust among the member UAVs.
Civil aviation authorities generally classify UAVs depending
on their gross weight. Based on the overall weight, the Civil
Aviation Safety Authority (CASA), Australia classifies UAV
systems in the following ways [27], [29].
i. Micro: Weighting less than 100 gms.
ii. Very small: Weighting more than 100 gms and less than
or equal to 2 Kgs.
iii. Small: Weighting more than 2 Kgs and less than or equal
to 25 Kgs.
iv. Medium: Weighting more than 25 Kgs and less than or
equal to 150 Kgs.
v. Large: Weighting more than 150 Kgs.
Depending on the altitude at which the UAVs are designed to
operate, they can be classified as follows [27], [30].
i. Low-altitude platform (LAPs): LAP type UAVs are suit-
able for fast and flexible deployment due to their high
mobility and cost-effectiveness. They are capable of flying
for several hours only.
ii. High-altitude platform (HAPs): HAP type UAVs are like
big gas balloons that have a long endurance up to days
and even months. Because of their large size and long
endurance, they have the capacity to cover a wider range
of areas in a single flight. Their attitude is generally above
17 Kms and they operate in a quasi-stationary nature.
Classification based on altitude is crucial in deciding the
type of operation of UAVs in case they are used for net-
work relaying. LAP UAVs are simpler and can be used to
assist in cellular communications, whereas HAP UAVs are
very complex in nature and are used in relaying Internet
connections. Companies such as Google and Facebook have
deployed HAP for such applications [31]. When such network
relaying happens in a very dense environment, to ensure there
is overcrowding of airspace and communication channel, it
is feasible to share one UAV that caters to the consumers of
all the network providers rather than each network provider
having their own UAV. Thus, using only a few shared UAVs,
catering to all the consumers is a better option. In this case, the
details of services provided can be stored over the blockchain
and as per the stored data, different network providers can
be charged respectively. Blockchain ensures trust between the
companies in such a scenario as we discuss in Section IV.
2) UAV regulations: Regulatory directives regarding the use
of UAVs in a particular area is an important topic as it is one
of the limiting factors in the deployment of UAV networks.
There are a lot of issues related to their operations such as
collision avoidance, data security, privacy, etc., which need to
be addressed and various UAV factors such as type, spectrum,
speed, etc., need to be looked into [30]. Broadly five important
categories must be looked into when working on the UAV
regulatory schemes [27], [32].
i. Applicability: It means the scope where the UAV regula-
tions have to be implemented. It may include UAV type,
weight, and role of the UAVs.
ii. Operational limitations: It refers to specifying the loca-
tions which are restricted for UAV operations.
iii. Administrative and legal requirements: This refers to the
set of rules and regulations put in place by the governing
body of the area to monitor the use of UAVs. These
predefined procedures and regulations must be followed
by the UAV operators in that area.
iv. Technology specifications/requirements: It refers to the
mechanical, communication and control capabilities of the
UAV. For a particular application, some requirements are
essential for the safe operation of the UAVs.
v. Moral and ethical issues: This mainly refers to the privacy
and security issues of the people at large.
B. Blockchain technology
Blockchain technology is a giant leap in the distributed
ledger technology. Its popularity has been ever increasing
since the release of Bitcoin, a peer to peer electronic cash
exchange system by Satoshi Nakamoto [33]. The blockchain
technology holds immense potential in other spheres where
trust is required between mutually dependent parties. Its utility
is not only limited to electronic cash exchange systems such
as Bitcoin, Litecoin, etc. but also includes making financial
markets smart [34] and enabling secure communication be-
tween robotic swarm systems [23]. Compared to centralized
forms of record-keeping, blockchain offers a lot of benefits
such as providing complete transparency of data and operates
without any failure. Blockchain provides anonymity, security
and also eliminates the need for a middleman or a third party.
If only one person owns the ledger, there exists a possibility of
committing mistakes, either accidentally or on purpose. While
if everyone in the system holds the ledger, i.e., if the ledger
is decentralized, cheating becomes difficult. We present here
an overview of the blockchain technology by discussing its
architecture and types.
C. Blockchain architecture
Fundamentally a blockchain is made up of six major layers
which are data layer, network layer, consensus layer, incentive
layer, contract layer and application layer [35], [125]–[129]. A
pictorial representation of the layers is given in Fig. 2. A layer
by layer description of the blockchain architecture is discussed
1) Data layer: The data layer is the bottom-most layer in the
blockchain architecture which contains the timestamped
blocks of data. Every data block consists of the block
body and the block header. The current block’s header
contains the previous block’s hash, and the next block’s
header contains the hash of the current block. In this way,
the blocks are chained together like a linked list. Fig. 3
shows the structure of a common block in a blockchain
[35], [125]. The timestamp marks the time at which the
corresponding block was created. The Nonce is a random
number added to the block by the miners to get the
desired pattern in the block-hash. Merkle root, as the
name suggests is the root of the Merkle tree. Merkle tree
stores the transactions within a specific period via a hash
binary tree mechanism.
2) Network layer: The purpose of the network layer is to
distribute, forward and authenticate the blockchain trans-
actions. Blockchains are commonly modeled as Peer-
to-Peer (P2P) networks, where the peers enjoy equal
TABLE I: Applications of blockchain in other emerging areas.
Technology References
Smart cities [35]–[38]
Smart grids and energy management [39]–[46]
Smart communities [41], [47]–[51]
Edge computing [52]–[58]
Cloud computing [54], [56], [59]–[76]
Internet of Things (IoT) [58], [59], [77]–[109]
Machine learning [110]–[113]
Deep learning [114]–[120]
Brain Computer Interface (BCI) [121], [122]
Smart Healthcare [123]
Industry 4.0 [124]
Data layer
Network layer
Consensus layer
Incentive layer
Contract layer
Application layer
Data block
Hash function
Chain structure
Merkle tree Asymmetric encryption
Time stamp
P2P network Communication
Ripple Tendermint PoET ....
Issuance mechanism Allocation mechanism
Script code Algorithm Smart contract
IoT Smart grid Machine learning
BCI Smart city Deep learning
Blockchain layers
UAV/Drones ......
This study
Fig. 2: Blockchain architecture comprising of the six layer model [35], [125].
Hashes and transactions
Block body
block hash
NonceMerkle root
Previous block hash
Fig. 3: Typical structure of a block in a blockchain [35], [125].
privileges. Once a transaction is created, it is broadcast
to the neighboring nodes for verification. This is done
based on pre-defined specifications. Once the transaction
is validated, it is sent to the other nodes and in case of
rejection, it is discarded. This ensures that only the valid
transactions are allowed to be recorded at each node. An
asymmetric cryptography mechanism based on the digital
signature is generally used to authenticate transactions
[35]. The digital signature scheme has two phases- the
verification phase, and the signing phase. Transactions
are generated by each node and digitally signed via
their private key and subsequently, other nodes use the
initiator node’s public key to verify the transaction’s
3) Consensus layer: It is a very important layer and com-
prises of different consensus algorithms which are re-
quired to reach a consensus among the untrusted parties
participating in the blockchain network. This is core to
the principle of blockchain technology as the consen-
sus among the participants is the key to avoiding the
need for a centralized entity. There is a need for some
protocols to ensure consensus among the participants of
the blockchain [130]. The major consensus mechanisms
[35] are Delegated Proof of Stake (DPoS) [131], Practical
Byzantine Fault Tolerance (PBFT) [132], Proof of Work
(PoW) [33] and Proof of Stake (PoS) [133]. Apart from
these, there are other consensus algorithms also such as
Tendermint [134], Ripple [135], Stellar [136], Proof of
Bandwidth (PoB) [137], Proof of Reliability (PoR) [138]
and many more. For more details regarding different con-
sensus protocols, readers are encouraged to go through
[35], [139], [140].
4) Incentive layer: The incentive layer can be called one
of the foundation pillars of blockchain architecture as
it the driving force behind blockchain’s usage and the
which it has today. It combines the blockchain technology
with economic factors and creates a mutually beneficial
scheme for the miners. The miners invest a lot of pro-
cessing power to mine the blocks and in return get reward
points in the form of incentives such as digital currency
corresponding to the magnitude of their work.
5) Contract layer: The contract layer makes the blockchain
programmable and enables the inclusion of different
scripts, smart contracts, and algorithms with the help of
which complex transactions can be carried out on the
blockchain. A smart contract is a set of rules which when
met triggers a transaction between the two parties in-
volved in the contract. When these parties agree with the
terms specified within the contract, it is cryptographically
signed and is broadcast to all other nodes participating in
the blockchain for verification [141].
6) Application layer: This is the highest layer of the
blockchain which comprises of its applications in var-
ious practical fields such as IoT, finance, AI, etc. We
discuss the applications of blockchain in UAVs in this
paper, which is also a part of the application layer.
There have been various studies related to applications
of blockchain in different fields such as smart cities
[35]–[38], smart grids and energy management [39]–
[46], smart communities [41], [47]–[50], edge comput-
ing [52]–[58], cloud computing [54], [56], [59]–[76],
Internet of Things (IoT) [58], [59], [77]–[109], machine
learning [110]–[113], deep learning [114]–[120], Brain-
Computer Interface (BCI) [121], [122], healthcare appli-
cations [123], Industry 4.0 [124] and many more. Apart
from this there are other innovative applications also
such as tracking and registration of police FIR [142],
mobile data offloading [143] and many more. A more
recent blockchain-based application was implemented by
authors in [144], where they developed a smart irriga-
tion system using blockchain technology. Table I gives
an overview of the applications of blockchain in other
emerging areas.
D. Blockchain types
Currently, blockchain systems have been broadly catego-
rized into three types based on the ownership and the audience
allowed to participate in the process of block verification and
addition [145], [146].
1) Public blockchain: In a public blockchain, all the records
are visible to the public and everyone is allowed to
take part in the consensus process, i.e., a permissionless
consensus process. Public blockchains have the highest
immutability as compared to the other two types since
the number of participants is very high [145]. However,
public blockchains have lower efficiency as compared to
private and consortium blockchains.
2) Private blockchain: In a private blockchain, only those
nodes which come from one specific organization are
allowed to join the network and the consensus process,
i.e., it has a permissioned consensus process. It is also
regarded as a centralized network since it is fully under
the control of one organization. Such networks have high
efficiency but can be tampered with relatively easily as
compared to public blockchains because of the lesser
number of participants.
3) Consortium blockchain: A consortium blockchain also
has a permissioned consensus process, but unlike a pri-
vate blockchain, only a few selected organizations can
participate in it. Therefore, it is a partially decentralized
system. It also has high efficiency but can be tampered
with relatively easily as compared to public blockchains
In most cases, blockchain-based UAV applications require
a private blockchain since they need to have secure commu-
nication between the participating members. For example, in
Section VII which discusses UAV-based surveillance networks
using blockchain, one of the case studies analyzed [25] is
based on Hyperledger, a permissioned blockchain where every
UAV that wants to join the surveillance fleet has to procure a
certificate of enrollment from a certificate issuing authority.
UAV networks also require to have some battery charging
schemes to improve their flight time for operations. There have
also been some studies in that direction employing blockchain
technology and smart contracts [147].
E. Motivation and Relevance
According to the Federal Aviation Administration (FAA),
commercial drones registered in the US totaled about 412,000
in 2019 [148]. Combined with blockchain technology, drones
carry a huge potential to disrupt the way we live. Blockchain
as a technology holds immense potential for furthering the
utilities of UAV-based applications. For example, according
to UNICEF around 73,000 deaths occurred in the disastrous
earthquake that struck Pakistan in October 2005. The
government, armed forces, and civil aviation authorities
displayed an excellent immediate response but had their
efforts been backed by advanced aerial networks using
drones, more advanced rescue missions could have been
carried out in remote villages [149]. Using blockchain,
governments across the globe can track the identities of the
UAVs flying in their territories. With the increasing popularity
of UAVs, their usage in metropolitan areas has been increasing
at a rapid rate. The next generation of UAVs must adapt
to operate in such an environment where there are a lot of
obstacles and possibilities of cyber-physical attacks. [150]
discusses the obstacle shadowing approach for Vehicular
Ad-hoc Networks (VANETs) in the urban environment. In
[151], the authors designed a blockchain-based framework for
drone-mounted base stations in a tactile Internet environment.
Also, with the upcoming 5G technology, UAVs have a big
role to play in their efficient deployment [152], [153]. Having
a reliable communication channel in UAV networks is very
crucial because of their high mobility and sparse deployment
[154]. As blockchain technology evolves, so does the UAV
industry. Application areas of blockchain are broad, from
security robots to delivery UAVs logging their activities,
thereby improving customer contentment. Law enforcement
can be improved by security robots logging information on a
blockchain by providing concise information. UAVs are here
to stay and will change almost every aspect of our lives. The
future of UAVs will contain everything ranging from asteroid
mining to very small inner-body autonomous vehicles. Some
UAV networks for edge computing
UAVs acting
as edge
Decentralized storage in UAV
Ground sensors downloading
data from blockchain
sent via
UAV air
data to
Supply chain management
Drone delivery
via blockchain
Record inventory
Scan RFID tags
Security of UAV networks
Secure communication
using blockchain
malicious UAVs
UAV observes
UAV surveillance applications
Alert sent to
UAVs from different parties cordinating
with each other via blockchain
Co-ordinated UAV services
and security
Fig. 4: Applications of blockchain in various fields of UAV networks which are discussed in this study.
of the applications of blockchain in UAV networks mentioned
in this paper are shown in Fig. 4.
There have been many studies in the past which explore
application of UAVs in fields such as telecommunications,
medical supply delivery, military applications, surveillance and
monitoring etc [155]–[169]. To the best of our knowledge, a
comprehensive survey of the combined application prospects
of UAVs and blockchain has not been discussed to date.
In this paper, we try to present a comprehensive survey
of applications of UAVs using blockchain. The breakup of
each section is such that we highlight the motivation behind
using blockchain and its role in enhancing the applicability of
UAVs for each application area. Also, where ever possible, we
discuss the detailed working of the system in each area. In the
end, we discuss the challenges involved in each application.
A. Motivation
Supply chain management requires many labor-intensive
tasks right from the production of commodities in industries
and factories to marketing and sales. Automating these tasks
with upcoming Industry 4.0 technologies such as Industrial
Internet of Things [170], [171], fog computing [172], UAVs
[173], etc. can help in reducing time and increase profits for
business enterprises. Application of UAVs in such scenarios
to perform tasks such as surveying the stock, collecting
data [174], dispatching products have been discussed before.
Automating these tasks not only increases the efficiency of the
work but also opens doors to cyber threats and attacks from
untrusted third parties. Blockchain can be used to create a
transparent and immutable system that can help in mitigating
such threats. Blockchain technology can be used in these
applications to enhance the trust and security of such systems
and to store data in an accountable way, which can be used
for inventory management and monitoring the production
trends. Such tasks require a dynamic collection of data from
multiple locations which is conventionally done by humans.
Due to human intervention, this process of inventory stock
control is prone to accounting errors and is not always carried
out in real-time. This is where UAVs can be employed to
assist industries in automating tedious tasks, such as the ones
performed regularly for preserving the traceability of certain
items and determining the inventory. As part of the Industry
4.0 revolution, such applications of UAVs are discussed in
[173]. This can be combined with the blockchain technology
to automate various tasks such as determining the validity
of information coming from untrusted third parties and au-
tomating transactions with the help of smart contracts. Also,
blockchain-based UAVs systems can be used to carry out
automated transactions between consumers and UAVs, where
UAVs function as autonomous agents, as discussed in [175].
In this case, blockchain helps the UAVs and other robots
participating in business activities to make decisions about
their actions and plan activities by interacting with each other
via a peer to peer network.
B. Role of blockchain
Blockchain provides a high level of transparency, security,
trust, and efficiency in the supply chain and enables the use
of smart contracts. Depending on the rules set in the smart
contract, the parties involved in the contract will interact with
each other. The agreement is automatically enforced as soon as
predefined rules are met. These smart contracts help in verify-
ing, facilitating and enforcing the negotiation of a transaction.
It provides a way of decentralized automation. In [173] the
authors present a UAV-based system to automate the inventory
and keep track of industrial objects which are attached with
RFID tags. This system uses a blockchain that receives and
validates the inventory data collected by the UAVs, ensures
their trustworthiness and also makes them accessible to the
interested parties. Some of the specific utilities of blockchain
are as follows.
1) Automating data storage and verification: The data
collected by UAVs performing tasks such as inventory man-
agement can be directly transmitted to a cyber-physical system
connected to a blockchain. Each block of the blockchain will
contain details of the inventory stock scanned by the UAVs and
the timestamp at which the block was added, thus information
about the flow of stocks can be stored and monitored easily.
The UAVs can be programmed to charge themselves and
conduct scans at regular intervals, thereby fully automating
the storage and verification process.
2) Automating transactions: Smart contracts can help au-
tomate certain transactions and processes which take place
regularly, such as the ordering of supplies when the stock of a
particular product has dropped below a certain limit. As soon
as some predetermined conditions are met, the smart contracts
are executed without any human intervention. This process is
explained in Fig. 5.
3) Automating decision making: Via use of smart contracts,
UAVs participating in multi-agent systems can be programmed
RFID card
UAV scans the
RFID tags
with onboard
RFID scanner
Data sent to
number of
Number of
Smart contract
Stocks ordered and
payment made to
supplier through
Stocks refilled
Product cartons
labelled with
RFID tags
Fig. 5: Sequence of events in automating transactions with
untrusted third parties using smart contracts.
to make decisions on their own. For example, in the application
of Ethereum blockchain-based UAVs discussed in [175], smart
contracts are used for transferring commands between the
UAV and other robotic agents which operate in business
processes among people. In such applications, only when one
agent completes its task the other agent can start its task. After
completion of the task, the UAV agent deposits a specific
amount of token as specified in the smart contract to the
next UAV agent in the process. Here, tokens are the digital
currency of the internal blockchain network through which
the agents are connected. When the other agent receives this,
the smart contract is triggered. In this way the communication
is automated. With the help of blockchain, fully automated
communications can be ensured between the UAV agents,
by which they can execute commands and collectively take
decisions that are otherwise difficult for one UAV agent to do.
C. System working
For supply chain applications discussed above, the structure
of the Ethereum blockchain is the most suited as it enables
the use of smart contracts. We cover two aspects of the
supply chain here - managing the stock in an inventory, and
dispatching the products. For inventory management, each
block in the blockchain can contain - the timestamp at which
the data was recorded, and the transactions that the UAVs
make for the products they have scanned. Each product type
has an account created for it in the blockchain network.
Depending on the number of Radio Frequency Identification
(RFID) tags they have scanned for a product, the UAVs
send information to these accounts. The product types are
stored in the cartons and each carton contains a pre-defined
number of products (say Q) which is pre-loaded in the UAV’s
Total number of products in the warehouse as
on 11:30
UAV scans the stock via RFID scanner and stores the number
of tags ( imposed on each carton), n and the total number of
products , Q x n in the form of transactions in a block . The
amounts over multiple blocks are added to get the total
number of products at any given time as shown.
RFID tags are put on the cartons. The quantity of products,
say Q in each carton is pre-loaded in the UAV for every
product type. So the amount of products is N x Q , where N
denotes the total number of RFID tags scanned (N= n1+n2…) .
Watch(Q=400) : 7,2800
Block ID
Previous hash
Tie(Q=500) : 4,2000
Block ID
Previous hash
Block ID
Previous hash
Shirt(Q=300): 6,1800
Watch(Q=400) : 9,3600
Tie(Q=500) : 3,1500
Watch(Q=400) : 4,1600
Tie(Q=500) : 5,2500
Shirt(Q=300): 5,1500 Shirt(Q=300): 4,1200
Block -1 Block -2 Block -3
N =20, Q =400 N =15, Q =300 N =12, Q =500
Data from
warehouse area 1
Data from
warehouse area 2
Data from
Warehouse area 3
Area 1
Area 2 Area 3
UAV scans warehouse in
multiple runs. In each
run it scans one area.
Fig. 6: Representational blockchain for inventory management.
memory. So, the number of products is calculated as n times
Q, where n is the number of RFID tags scanned by the UAV
in one run. The number of tags added over multiple runs
gives N, the total number of tags scanned (calculated as N
= n1+n2+n3..). For example, in Fig. 6 the total number of
RFID tags scanned for product type watch is 20 (7+9+4) and
the corresponding calculated the total number of products
is 8000 ( 2800+3600+1600). So the balance in the account
dedicated to the watch product type is 8000. The balance of
the amount denotes the number of products. Each stock is
stored in cartons and each carton has an RFID tag associated
with it and the UAVs are equipped with RFID scanners [173].
When the UAVs scan the carton, their IDs automatically get
stored in the on-board memory. Due to the limited flying
time of UAVs and huge areas of warehouses, the warehouse
can be divided into multiple areas and a UAV can scan them
in multiple runs as shown in Fig. 6.
The UAVs are guided by fixed way-points to follow a
definite route along which they can scan the products in
the inventory storehouse. A similar concept of way-points is
also used in [175] where various dispatcher services reserve
air routes for UAVs via way-points. Using topographic data,
dispatchers trace a route and send it to the blockchain to be
received by the UAVs through a transaction. The sequence of
events starts with a request for delivery based on which a smart
contract is issued containing information about the order, its
purpose and the client data. This contract is accepted by any
UAV agent which is available. The client and the UAV agent
conclude a smart contract for air tokens which contains the
client’s location data. The UAV then commits the transaction
to request for air route to an agent dispatcher. As soon as
the dispatcher agrees to this contract, a new contract takes
place between them which has information about the registered
route. After this, the UAV makes the scheduled flight and
informs the dispatcher that the air route has been used.
D. Challenges
Inventories usually have a huge stock of products, hence
having RFID tags for all of them may be quite costly.
Furthermore, the blockchain being used for these applications
would require high processing power for mining the data and
creation of blocks which will also increase the installation cost
of the system. It will constantly consume electricity reducing
the efficiency of the system by increasing the operational
cost. In many countries of the world, the legal status of
blockchain-based cryptocurrencies such as bitcoin usage is not
very well defined. Thus, automating economic processes with
blockchain-based UAVs without a legal framework in place
can raise concerns in the future, leading to confusion and a
lack of trust among the participants.
A. Motivation
With the increasing popularity of UAVs, their application
areas are becoming more diverse and in many cases, a
group of UAVs performs the tasks rather than a single
UAV. Some examples of this are disaster relief, surveillance,
network relaying, energy-efficient device discovery [176] etc.
Coordination between the UAVs is core to these applications
but most of the existing systems lack a global knowledge-
sharing platform between the member UAVs in the UAV
network and instead just rely on local communication between
adjacent member UAVs [23]. This is where blockchain can
prove to be beneficial and it opens a new stream of
research in UAV networks emphasizing a global channel
for communication. Furthermore, with its help, we can
incorporate capabilities such as distributed decision making
and enhanced security into UAV networks. Some basic
requirements of coordination between UAVs are to prevent
mid-air collisions, to make decisions based on data collected
from more than one UAV and to securely communicate with
each other. Blockchain can help to provide secure one to
one as well as broadcast communication facilities in such
UAV networks with the help of public key and private key
mechanism. It can also empower the UAV network to make
decisions based on the opinion of other UAVs such as in
a voting system discussed in [23]. [23] also discusses the
application of blockchain to create new business models
where UAVs can conduct money transactions with human
users in exchange for the services they provide.
Another important area where blockchain can be used is
to coordinate activities between UAVs belonging to different
service providers in case of high demand which cannot be
met by any single party at a time. Such an application of the
operability of UAVs is discussed in [177]. This is called inter-
service operability of UAVs i.e. sharing a UAV among multiple
vendors to serve users present in a very densely populated area.
The coordinates of the UAV should not overlap to maintain
minimum interference. Taking into account the number of
users present and the services demanded by each one of them,
every vendor deploys a sufficient number of UAVs that are
capable of serving the users without any overheads. However,
multiple vendors may aim at providing the same solution,
therefore, there are good chances of channel blocking, inter-
ference, and overlapping coordinates. The network can fail
because of the above-mentioned issues. There should be a
platform that is capable of connecting UAVs from different
vendors but it involves issues related to authority, control, and
trust. A small glitch in the security is enough to disclose the
security protocol used by any specific vendor. Also, unreliable
and untrustworthy aerial vehicles may get associated with the
network leading to information leakage and redirection of
network traffic, causing losses to the vendors. There is a need
to handle such issues effectively without completely relying on
a central system which may induce operational overheads and
bottlenecks in rendering services. This issue can be resolved
using blockchain with very little overheads and complexity.
An aerial blockchain can be formed by UAVs from different
vendors, creating a social circle of UAVs as described in [177].
B. Role of blockchain
Blockchain technology can provide reliable peer-to-peer
communication channels to UAV networks (UAVNETs) and
ways to overcome possible threats and attacks. We discuss
Block header
Time stamp
UAV 1 public key abc1234
UAV 1 encodes
message with its
private key
UAV 1 private key def6745
Other UAVS in network
decode message with public
UAV 1’s public key abc1234
visible to all UAVs in
Nth Block
N+1 Block
Fig. 7: Digitally signing the data with the help of public key
for broadcast communication.
below some of the utilities of blockchain specific to coordina-
tion in UAV networks.
1) Creating new business models: A combination of
UAVNETs and blockchain can be used to develop new busi-
ness models that incorporate the facility of exchanging data
between a UAV and an end-user. Sensing-as-a-Service (S2aas)
is a business model in the Internet of Things (IoT) field which
is gaining a lot of popularity [178]–[180]. It helps in creating
a market pattern in which multiple users can buy sensor
data from multiple sensors. Having a blockchain incorporated
in this network will make the process decentralized and
autonomous. A possible model of such an implementation is
discussed in [23].
2) Collision free movement of UAVs: One of the most
important requirements in UAV networks is that the UAVs do
not physically crash into each other and also that they do not
interfere with each other’s signal. Blockchain can help achieve
this feature by storing the coordinates of all the UAVs in its
database. By using algorithms such as discussed in [181] and
referring to these stored coordinates, UAVs can decide their
optimal route to move to a destination without any collision
and with minimum interference.
3) Uniform load sharing: In inter-service operations, it is
necessary to ensure uniform distribution of services between
different vendors who lack trust among each other. Blockchain
can solve this problem owing to its being a transparent
electronic ledger. Based on the load information of different
regions, UAVs can be assigned their regions of operation
ensuring uniform distribution as far as possible. Another way
to do this is to assign a set of randomly generated non-
overlapping coordinates which can be used in cases where
the load is dynamic. This technique can also be used for load
balancing in UAV assisted communication for IoT [182].
4) Data and entity authentication: Because of the facility
of the public and private key, UAVs can communicate with
each other through a common channel and avoid hacking
of data by third parties who can get access to the channel.
Additionally, they can also uniquely sign the data collected
using their private key and can broadcast it to the whole
network. This way, blockchain also helps in enabling the
feature of a digital signature as shown in Fig. 7. This provides
data source and entity authentication between the UAVs and
UAV 1 Encodes
message with
public key of
UAV 2 : xyz4567
Block header
Time stamp
UAV 1 public key abc1234
UAV 2 public key xyz4567
UAV 2 Decodes
message with
its private key
UAV 2 private key opq1896
Uh! I don’t
know the
decoding key
N+1 Block
Nth Block
Fig. 8: Sending encoded data for one to one communication
using the public-private key feature of the blockchain to avoid
data theft [23].
third party agents as the origin of the data can be traced using
this feature. This is very crucial for disaster relief operation
and in health care applications such as the I-ward project
which uses robot teams to assist health workers [183]. Also,
in applications such as exploration using robotic swarms, this
can help in uniquely identifying the robot which made the
discovery and storing the timestamp at which it was made.
5) Cooperation and fast synchronization: By having a
common communication channel in the form of a blockchain,
UAVs can make requests for assistance from other UAVs
or other robots in the swarm in emergency cases such as
a low battery, system faults, sensor malfunction, etc. Also
using distributed decision making, they can get the opinion
of other UAVs and decide the case of confusion and such
decisions can be stored in the blockchain for the new members
who join the swarm. They can directly download the ledger
containing previous decision histories and synchronize with
the swarm instead of being trained specifically which saves
a lot of time and processing power. This can be very useful
for military applications where the probability of casualties of
swarm robots maybe can be high. Also, such applications may
be conducted in a multi-terrain environment where robots may
be of different kind and ground robots may request an UAV
to make them cross a river. Such a case is discussed in [23].
Also, UAV systems Blockchain can also help in maintaining
cooperation between different swarm systems from competitor
parties when they operate in the same environment. With the
help of blockchain, they can share a common communication
channel as shown in Fig. 8 and securely share their confidential
data within the network.
C. Working of blockchain application in UAVNETs
UAV networks (UAVNETs) can be employed in a wide
range of applications depending on which the structure of
blockchain can change from case to case. [23] discusses an
example of distributed decision making where a UAV network
is deployed for search and identification purposes. When a
particular UAV faces confusion on the identification of an
object, it shares it in the network and other UAV members
can vote on the identity of the object. Based on the majority
of votes, the actual identity of the object is ascertained and
this data is stored in the blockchain for future reference.
However, various other blockchain structures can be designed
depending on the application. In most of the applications, each
UAV acts as a node in the blockchain, capable of adding
the records without overwriting. In the case where UAVs
from multiple parties are involved such as in inter-service
operations, a concept of weights is also used as discussed in
[177]. Depending on the load each UAV caters to, a weight is
assigned to it which acts as a criterion for deciding who has
more control over the blockchain in cases like forks (forks are
like software updates in an operating system). A blockchain
may also undergo a change of rules and policies which is
called a fork. Having a weighted system ensures who has more
control over the forks. On similar lines, there are many new
concepts that can enhance the utility of blockchain in practical
scenarios. We discuss the working of some of the application-
specific cases below.
1) Distributed decision making mechanism: By having a
common communication channel in the form of a blockchain,
UAVs can make distributed decisions.An elaborate mechanism
is presented in [23] where any UAV that is faced with
confusion between some choices creates new addresses in
the blockchain network. Each address represents one of the
options for the decision. The other UAVs in the network
will make a transaction of amount 1 or 0 to one of these
newly created addresses depending on the option they choose
based on their discretion. In the end, the address which has
the maximum balance in its wallet is chosen. In this way,
the entire UAV network participates in decision making. The
decision is also broadcast to the whole network so that each
UAV knows what decision to take when a particular situation
arises again.This mechanism is also explained in Fig. 10.
2) Secure communication channel for swarms: Blockchain
can provide reliable peer-to-peer communication channels to
swarm agents and ways to overcome possible threats and
attacks. In the blockchain encryption scheme, public-key cryp-
tography and digital signature schemes are used. A pair of
complementing keys called public and private keys are created
for each agent to provide the required capabilities. Public
keys are like account numbers which are publicly accessible
information and private keys are like passwords or secret
information which will be used to authenticate an agent’s
identity and the functions that it executes. In the context of
UAV swarm systems, digital signature scheme and public-key
cryptography are shown in Fig. 7 and 8 respectively. Any UAV
can send data to any other UAV in the system since the public
keys of all the UAVs are known to all other UAVs. But only
the UAV whose public key is used to encrypt the data will be
able to decrypt it since private keys are private to the individual
UAVs. Since the public key cannot be used for decryption, it
secures the message from third parties even when they use the
same channel.
3) Inter service operability of UAVs: For providing services
to users present in an ultra-dense environment it is more
sensible to have fewer UAVs in the region that cater to all the
users instead of each service provider having its UAV catering
to a few users. In the latter case, there will be a high probability
of signal interference, UAV collisions, channel blocking, etc.
Different vendors collaborate and
operate via a shared network of UAVs.
UAVs in this network store information
about the data traffic and service time
of each vendor in the form of
transactions in the blockchain. Every
vendor or service providers (SP) has
its unique address (public key) against
which the data is stored. This can be
later compiled as shown in the graph
and the revenue can be divided
400 300
SP - A (1fgh23) SP - B (3abc78) SP - C (8ytr98)
Vendor wise services for time T1 to T3
Data traffic (in GBs) Service time (in minutes)
Block header
Time stamp T1
100 GB 1fgh23
100 GB 3abc78
500 GB 8ytr98
Block header
Time stamp T2
800 GB 1fgh23
400 GB 3abc78
700 GB 8ytr98
Block header
Time stamp T3
400 mins. 1fgh23
300 mins. 3abc78
700 mins. 8ytr98
Block ID
Block header
Public key of
Data block Data block Service time block
……. ……. …….
Fig. 9: Representational blockchain for coordinated services using UAV networks.
UAV is confused whether the image
is of a thief or common man
2So it creates two addresses in the blockchain
network for the two choices by making a
transaction of amount zero to them:
A- Thief
B- Common man
3Other UAVs in the network vote in one of
these two options based on their past
experience. Voting is done in form of
transactions of amount 1 or 0 to
addresses of A or B.
The option which receives the maximum votes
is accepted as correct by the UAV.
A- Thief B- Common man
Fig. 10: Working of a distributed decision making mechanism
in a UAV network using blockchain [23].
In such cases, few UAVs from multiple vendors can unite to
form a blockchain and provide coordinated services to the
users. As the vendors might be competitors in the market,
with the help of blockchain they can maintain the level of trust
among themselves. Another application is discussed in [177]
where the authors use the concept of a weighted blockchain
for load balancing in UAVNETs. Load balancing can be
implemented using consensus between different UAVs from
different vendors and the users are charged depending on how
much services they utilize. Fig. 9 shows a representational
blockchain where the data usage and the service time are
stored in the blockchain in the form of transactions that the
UAVs make to the vendor’s account. Identification of vendors
is carried out and zones are allocated to each of the identified
vendors for cooperative operation over a region. The UAVs
use a public key for identifying each other without the need
of any centralized authentication mechanism. When all of
the vendors together approve for delivering services in a
particular region, they share private keys with each other which
are required by the UAVs to exchange the load information
when multiple UAVs are communicating. The vendors are also
allowed to change the private keys if there exists a situation
of possible threats. For accessing the broadcast information
the private keys are required for knowing the access rights
on that information. These policies are driven by the service
agreement between the service providers. For the location-
allocation to each UAV of different service providers, there
are two methods discussed below.
i. A UAV may serve at a stationary point where its sole
purpose is to serve as a High Altitude Platform System
(HAPS). Here the UAVs do not have to move over the
ii. A UAV may serve a set of coordinates where the UAV
has to maneuver around a particular allocated region.
The performance factors of such networks as discussed in
[177] show that blockchain-based solutions to such problems
have low operational overheads, low latency and are less costly
as compared to other traditional and centralized deployment
techniques. Thus we can see that blockchain-based UAV
networks are better compared to other methods used.
D. Challenges
Although the integration of UAV networks with blockchain
opens a lot of possibilities, there also exist many practical
challenges [23]. In Bitcoin, a block takes almost 10 minutes
to be processed. Although such a delay can be minimized
in private blockchains, there will still be a significant time lag
between the time when the transaction is carried out and when
it is confirmed. This can prove to be dangerous in carrying out
cooperative tasks between the UAVs such as swarm movement
and can cause collisions. Also, if the number of UAVs in
the swarm is very large and can operate for a long period of
time, the blockchain itself can grow very large for the UAVs
to accommodate. This problem is also faced by the Bitcoin
community and is called bloat [184].
A. Motivation
IoT technologies have advanced a lot in recent times with
their applications in many industries such as agriculture, envi-
ronmental monitoring, security surveillance,logistics services,
heath care monitoring, diasater monitoring, production process
etc. The number of devices connected to IoT is going to
increase a lot in coming times and technologies such as fog
and edge computing will be crucial for supporting it [185].
There have been also studies to improve the security and
efficiency of IIoT systems [186]. UAVs are an integral part
of such IoT applications and are used as active platforms
for deploying sensors in the air. Being vulnerable to security
attacks is a hindrance in their wide-scale adoption [187].
This is where blockchain technology can be helpful since it
provides a distributed storage mechanism which is secure due
to usage of cryptographic techniques such as hash functions.
We discuss the model presented by [187] where the authors
propose to use blockchain for creating a decentralized storage
architecture for air to ground industrial IoT networks where
both the Air Sensors (ASs) and the Ground Sensor Modules
(GSMs) can participate in a mutually beneficial exchange of
data. Blockchain’s peer-to-peer (P2P) approach thus could play
an important role in the development of IoT decentralized
systems. Its objective is to design an air to ground P2P data
transfer network in which UAVs mounted with ASs can send
the cached data from air to GSMs in an efficient, secure and
decentralized way.
B. Role of blockchain
The role of blockchain here is to securely store and send
data from the UAV nodes (on which ASs are deployed) to the
GSMs. Blockchain also helps in distributing rewards (such
as crypto-currencies) from UAVs to GSMs depending on the
services they provide such as storage and processing power,
and thus enables the creation of a mutually beneficial model.
Blockchain provides the following utilities for this application:
UAV broadcasts request
for storage.
Ground sensor module in
closest proximity responds.
Air senors onboard
UAV collect data in
hij675 try342 abc123
UAV sends reward
points to the address
abc123 of the ground
sensor module via
UAV sends data
to the ground
sensor module.
Different ground
sensor modules
with their public
Ground sensor
module sends ACK
after complete
Fig. 11: Ground sensor modules and air sensors (onboard
UAVs) participating in a blockchain empowered decentralized
storage system. Various smart devices installed in offices,
homes, buildings, vehicles, streetlights, etc., can be equipped
with sensors to act as ground sensor modules [187].
1) Increase air data security: The GSMs which are part
of the network allocate caching space to the UAVs to collect
and secure their data. The UAVs in return pay the GSMs with
reward points with the help of transactions in the blockchain.
The UAVs can instantly transfer the cached data to the GSMs.
This reduces the vulnerability of the data collected by the
UAVs since the adversaries will have a lesser window to carry
out physical or cyber attacks.
2) Enable mutually beneficial transactions between hetero-
geneous IoT agents: The UAVs can pay the GSMs for their
services of securing the data collected by ASs onboard. The
GSMs provide additional storage space and processing power
to the UAVs with ASs and in return the UAV pays them with
reward points, thus creating a mutually beneficial network. The
authors of [187] also point out that such a mutually beneficial
network will create a healthy ecosystem in a heterogeneous
IoT environment as shown in Fig. 11. Heterogeneous IoT
systems is a growing area of research [188] and have the
potential to transform the lifestyle of individuals.
3) Tackle problem of limited storage and processing power
onboard UAVs: UAVs harbouring ASs have limited storage
space and processing power. By sending the data collected
by ASs to GSMs they can free up their onboard memory to
capture the next set of data and also save the data processing
power. Saving on power can increase their flying time.
C. System working
Following is the sequence of operations which take place
in such an air to ground industrial network:
i. The first step of the system is the collection of data by
ASs present at different altitudes.
ii. An UAVs with AS requests for storage space from the
GSMs by issuing a broadcast command.
iii. The GSM having the closest physical proximity to the
UAV offers its storage space.
iv. Data is sent from the UAV to the GS.
v. GS receives the data and verifies the completion of data
reception with an acknowledgment signal.
vi. The UAV issues reward points to the GS via the
The transactions between the UAVs and the GSMs are
carried out using smart contracts and the consensus protocol
used is the Proof of Space (PoS) as discussed in [189].
The blockchain structure used is based on the IoT security
blockchain-based framework discussed in [77] which has a
block header, block data and a policy header.
D. Challenges
The proposed system of organizing air to ground industrial
IoT networks with the help of blockchain is a very innovative
solution but its implementation still faces some challenges.
As air sensors are installed in the air, regulatory concerns
come up with government and airspace rules of the region.
The reward that is given out in the form of cryptocurrency is
again a concern with countries such as India banning private
cryptocurrencies completely. Also, organizing a diverse set of
ground sensors modules can be a big challenge as various
types of individual and commercial enterprise permissions will
be required to install ground sensors modules on their property.
A. Motivation
The use of UAVs has been increasing at a huge rate across
industries for both defense and civilian applications. With
further advancements in the technologies used for making
them, such as battery capacity, AI-based software solutions,
physical design improvements, construction material, camera
technologies, etc., their demand is going to increase manifold
[190]. This increases the risk of cyber-physical attacks on
the UAVs in the coming years especially once their usage
is regularised by governments across the globe. Blockchain
technology has the potential to secure data that is being
dynamically updated, through its security capabilities such
as hashing, smart contracts, consensus protocols, public and
private keys, etc. Hence it is ideally suited for UAV applica-
tions which are very dynamic in nature. As the UAV traffic
density in the air increases, there is an increasing need to
integrate them with the Air-Traffic-Control (ATC) network
to regulate their movement and usage. This can be achieved
with the help of blockchain as discussed in [190]. UAVs can
decide their flight routes independently with the help of their
onboard blockchain copy containing information about flight
routes of the other UAVs and the input data from ATC. In this
section we discuss the security models presented by [190]–
[192] to analyze the applicability of blockchain in addressing
the security challenges of UAV networks. Fig. 12 gives a
pictorial overview of different scenarios where blockchain can
enhance the security of UAV networks.
B. Role of blockchain
1) Mitigating jamming of UAV signals: Jamming of wireless
signals between the UAVs and the Ground Control Station
(GCS) can be fatal if the flying control and navigation
systems are dependent on the commands from the GCS.
It can be a single point of failure for the whole system.
Having a decentralized blockchain network removes this
dependency and reduces the vulnerability of UAV net-
works to signal jamming. Each UAV has a copy of the
blockchain which contains the flying route details of other
UAVs and can decide its path accordingly.
2) Detecting UAV hijacks, poisoned data and ensuring data
integrity: UAV networks are very vulnerable and dynamic
in nature. An adversary UAV may enter the network and
start injecting false information or alter the original infor-
mation. Such altered information called poisoned data can
also be injected by UAVs which were initially part of the
network but were later hijacked by adversaries. To tackle
such attacks, the consensus mechanism of blockchain can
be implemented. If any UAV detects suspicious activity, it
can report it in the blockchain and if the number of such
entries against a UAV exceeds a certain predetermined
threshold, it can be concluded that it is a malicious UAV.
Also, in commercial scenarios, blockchain can be used
to receive the feedback of end-users to enable the UAVs
to reach a consensus on the source of internal attacks, if
3) Avoiding mid-air collisions of UAVs: UAV networks may
comprise a large number of UAVs with a high probability
of their routes clashing with each other due to a slight de-
lay in the command signal received or a channel blockage
in the path of the signals coming from GCSs. If each UAV
has an onboard blockchain copy containing the flying
routes of its peer UAVs, it can maintain a safe distance
from others while moving towards its destination. This
removes the dependence of UAVs on manual signaling
which is highly prone to delays and errors.
4) Securing UAV communications: The communication in-
frastructure in UAV networks is prone to threats such
as spoofing, Denial-of-Service (DoS), man-in-the-middle,
eavesdropping, and data tampering attacks as discussed
in [192]. Blockchain empowers the UAV networks to
encrypt the data and store them in the blockchain thus
making it inaccessible to anyone without the legitimate
decryption key. In [192], the authors have proposed a
mechanism where one of the UAVs is responsible for
block creation (called the ’forger node’) and all the
other UAVs are used for block validation and verification
using the Proof of Stake (PoS) consensus protocol. The
selection of a forger node is done using a utility function
based on game theory. The presented study shows that
the blockchain security model gives better performance
compared to other state-of-the-art security systems in
place for the UAV networks in terms of communication
latency and cost.
5) Securing UAV data types: In any UAV network there
are four main data types namely, UAV identifier, flight
Data stored on
the blockchain
Avoiding mid-air
collision of UAVs
Securing drone
Securing UAV
data types Decryption
Flight route control
Sensor data
Flying schedule
Blockchain enabled
autonomous UAVs
capable of taking
their own decisions
Securing data
dissemination to
end users
Detecting hijacks,
poisoned data and
ensuring data integrity
Mitigating signal
Security applications
of blockchain in UAV
End users
UAVs lost due to
no control signal
from the GS
Blockchain detects
malicious UAVs
preventing injection
of poisoned data
station (GS)
Fig. 12: An overview of security applications of blockchain in UAV networks.
route control, sensor data, and the flying schedule [190].
Blockchain provides secure storage and protects the in-
tegrity of these data parameters by writing and updating
them inside a block of the blockchain. The authors of
[190] show us how the flying schedule and the flight
route control of the UAV can be implemented in the form
of a smart contract. The fulfillment of the conditions in
the smart contract indicates the completion of the UAV’s
flight mission.
6) Securing data dissemination: Data dissemination refers
to the distribution of data to the end-users. The forger
node (as discussed in the previous section) sends the data
to the end-users to securely store it in the blockchain.
The following sequence of steps is followed for the same
i. Forger node encrypts the packet data to be sent and
forwards it to a public distributed blockchain.
ii. The public distributed blockchain network accepts
the request and updates its ledger.
iii. Forger node computes the digital signature of the
packet data with its private key.
iv. This digital signature is then broadcast to the public
blockchain network.
v. The distributed nodes verify and validate the broad-
casting node.
vi. Post validation the packet is forwarded to the end-
vii. The end-user decrypts the packet with the public key
of the forger node and sends an acknowledgment
(Ack) to the forger UAV, indicating the completion
of the transaction.
In this way, blockchain can be employed to secure the
communication between UAVs and end-users. This is
important for future commercial applications of UAV
networks in areas such as Sensing as a Service (SaaS)
[178]–[180] and new business models such as UAV
C. Challenges
1) Limited resources onboard UAVs: Like any other existing
blockchain applications, the models discussed here also
come with certain limitations of data storage, computation
time and computation cost. As the number of UAVs in
the network increases, the computation cost also goes up.
And as more data is generated, the blockchain becomes
bigger occupying a lot of disk space. Also hashing for
larger data requires more time and processing power
which is limited onboard UAVs. Given that UAVs al-
ready have a lot of onboard processing requirements for
controlling their flight and other attached payloads such
as cameras, sensors, etc., simultaneously carrying out
computations for blockchain will be a big challenge.
2) 51 percent attacks: Blockchain networks are also vul-
nerable to attacks from mischievous groups who can
gain control over the majority of the mining power of
the blockchain(i.e. control over 51% of the participant
nodes). This gives them freedom to create a fork in the
chain and ability to revert transactions which took place
when they were in control of the blockchain. They can
also prevent certain transactions from getting registered
in the blockchain. In UAV networks, adversaries can
prevent the UAV’s coordinates form getting registered on
the blockchain or even delete them with the help of a
51% attack. This can be fatal for vehicles in air such as
commercial airplanes and also harm people and property
on the ground.
3) Rigorous mathematical testing: Implementing blockchain
models in UAV networks is a very complex task. Rigor-
ous simulations have to be carried out keeping in mind
various test cases that may be possible. The whole system
design needs to be verified from all angles before the
technology moves into real-life implementation, since any
error may lead to fatal accidents. Although simulations
have been carried out by [191] with positive results,
more robust testing from the system engineering point
is required which is very challenging to carry out in such
complex UAV networks.
A. Motivation
UAVs are being actively explored for their usage in surveil-
lance applications because of their high mobility and dynamic
nature which empowers them to operate in regions without
any network infrastructure such as borders, remote environ-
mentally sensitive locations and regions affected by natural
disasters [193], [194]. However, because of their dynamic
topology, UAV networks have many security challenges that
make them vulnerable to a variety of attacks. Some of the
main challenges faced by UAV networks are as follows [25].
i. Trust and data authentication.
ii. Upholding the security and reliability of channels.
iii. Finding the optimal path.
In areas without any Vehicle to Infrastructure network
(V2I), UAVs rely on their Vehicle to Vehicle (V2V) networks.
This communication needs to be secure as they are used in
real-time mission mode applications such as combat [195],
border monitoring, and rescue and relief operations. Thus, it
is important to know what kind of attacks can penetrate their
communication network to appreciate the role of blockchain
in solving them. The most frequent and popular attacks made
on such networks are listed below [25].
i. Unauthorised access to the UAV ID and physical location
of UAVs.
ii. DoS attack.
iii. Sybil Attack which creates confusion in the network by
imitating several UAVs with the same ID.
iv. Increasing the latency of system transmissions by spam-
v. MITM attack.
vi. Blackhole attack.
vii. Fake information of locations.
Blockchain can very easily secure access to the IDs and
physical coordinates of UAVs as is discussed in one of its ap-
plications of securing UAV data types in the previous section.
It can easily avoid MITM attacks by encryption and decryption
mechanism using public-key cryptography. Given the consen-
sus mechanism of UAVs participating in the blockchain, it is
also not difficult to detect fake information. Thus, blockchain
has the potential to solve most of these problems and can be
used to securely and efficiently implement these mechanisms.
Surveillance is not limited to only military applications but can
be conducted in the civilian environment also ( e.g., traffic
management in metropolitan areas, imaging of a particular
area, etc). Such applications do have a ground infrastructure
but operate in a highly dense environment which means there
is a lot of physical obstacles in the movement of UAVs and a
lot of scope for high jacking of the data transmitted between
them. Thus, blockchain can be used to enhance the security
of such UAV ad-hoc networks and avoiding paths where the
line of sight is blocked. Blockchain can also help in detecting
wrong information when a UAV is hijacked physically using
asymmetric encryption and discriminate such compromised
UAVs using distributed trust management. We discuss the
system models presented in [25] and [24] to discuss this
application of blockchain in UAV surveillance applications.
B. Role of blockchain
Blockchain ensures the security of information sets by shar-
ing them and verifying the data by the distinctive suggested
parties. It can help in creating a robust data transmission
network between UAVs where data can be verified at various
checkpoints to ensure the integrity of the data. Also, using the
features of unique fingerprint of every block (in the form of
hashing) and the addressing mechanism (in the form of public
keys and private keys), the robustness of the system can be
increased against attacks by adversaries. Thus, on similar lines
we discuss some of the utilities of blockchain in surveillance
applications below:
1) Maintaining high trust of intruder detection alarm:
One of the main purposes of deploying UAV systems for
surveillance is to create an alarm in case of intrusion of
surveillance areas. Blockchain can facilitate the verification of
such intrusion events and maintain high trust of the alarm.
Every time an event occurs, UAVs detect them and pass
on these messages to neighboring UAVs by adding a block
Time stamp
Intruder alert !
ID: UAV A (Directly
Height: xxxxxx
Previous hash
Intruder alert !
ID: UAV F ( Indirectly
Intruder alert !
ID: UAV C ( Indirectly
True alarm
Intruder entering
the surveillance
UAV A is the first one to
observe the intruder
UAV B,C,D,E and F in A's
vicinity indirectly observe via
UAV A's alarm and inform other
UAVs in the network.
Block generated by UAV A
Block generated
by UAV F
Block generated
by UAV C
Time stamp
Intruder alert !
ID: UAV A (Directly
Height: xxxxxx
Previous hash
Intruder alert !
ID: UAV F ( Indirectly
Intruder alert !
ID: UAV C ( Indirectly
False alarm
Malicious UAV A generates
false alarm and similar
sequence of events take
place as in case of real
Block generated by
malicious UAV A
Scenario with real intruder in surveillance area Scenario with a malicious UAV raising false alarm
4Information spreads in
the whole network.
As the inruder moves further in
the surveillance area UAV B and
C will observe it directly and
hence the trust level of alarm
increases with time in case of a
real intruder.
Trust level Of
alarm i.e. number
of direct observers
Here with time the number of direct
observes will remain only one and
hence unlike in case of a real intruder,
the trust level of the alarm remains
Trust level Of
alarm i.e. number
of direct observers
Fig. 13: A blockchain-based surveillance system [25]. (Left) Raising of alarm in case of a real intruder and (Right) a malicious
UAV generating a False alarm. The trust level of true alarm increases with time whereas the trust level of false alarm remains
to blockchain containing details of the intrusion and this
continues recursively as shown in Fig. 13. Each UAV sends
different encrypted messages conveying whether they detected
the intruder directly or is it done by another one and If several
UAVs observes the same intruder event, it can be validated
and if the event is detected by only one UAV it is taken as
true, but considered suspicious. Like in Fig. 13, in case of a
real intrusion the first UAV to observe it is UAV A and then
subsequently UAV B and UAV C will also observe it and hence
the trust level of the alarm increases. But in case of a false
alarm, only one alert is obtained and its trust level remains low.
Also, if it is detected that a UAV has sent false information, it
is penalized and loses its trust. The neighbor UAVs can find out
if an UAV is sending malicious data continuously as each UAV
keeps updated track of IDs of all the direct observers. A similar
implementation based on the principles of blockchain was
simulated by [25]. The results of the study show that in case
of an actual intruder crossing surveillance area, the number of
direct observer UAVs remains below 10 percent throughout the
time period of simulation and the number of indirectly alerted
UAVs reach 100 percent in about 50 minutes and within an
hour the trust level of the alarm reaches 90 percent in the
network. In the case of an intruder, UAV generating a false
Alarm of tress-passing the indirectly alerted UAVs reach 100
percent in an hour but the trust level of the alarm remains 0
as only one UAV reports it. So overall the performance of the
system if satisfactory and the distributed trust policy proves to
be beneficial in detecting false alarms. This is a very essential
feature of a surveillance network because if the alarm loses
its trust then cases of real intrusion may go unnoticed.
2) Securing the surveillance data from adversaries: Se-
curing the surveillance data captured by the UAVs using
Blockchain makes it immune to impersonator UAVs or hackers
who may try to modify or access the data. Hashing mechanism
of blockchain protects the data from being manipulated. Hash
is a unique identity of each block which is generated by
inputting the data of the block to a complex mathematical
function. So even if there is a slight change in the data of the
block it will give an entirely different hash. So if an intruder
UAV wants to modify the data stored in the blockchain, then he
will have to recalculate the hash of the majority of the blocks
in the blockchain which requires huge processing power which
is not possible on-board an UAV. Another possibility is that
the malicious UAV may try to create a false alarm, this is
already discussed in the previous point where it is mitigated
with a distributed trust policy. Also to address the challenge
of authentication of UAVs joining the surveillance fleet, the
authors in [25] proposed to use the hyper-ledger permission
blockchain where every UAV which wants to connect to
the network needs to obtain an enrollment certificate from
an enrollment Certificate Authority (CA) that is part of the
membership services. The CA gives the UAV permission to
connect to the network and a transaction certificate which
allows it to submit transactions to the blockchain. Thus it
helps in increasing the authenticity of the surveillance data.
This is important because adversaries may try to tamper the
surveillance data to delete their mischievous acts which may
have been captured by the surveillance network.
3) Reduce system vulnerability to cyber-physical attacks
and physical obstacles: With the help of Blockchain, we
can implement a double-blocks checking mechanism which is
discussed in [24]. The mechanism is shown in Fig. 14. Here
different colors represent different blockchains and each node
represents a UAV which adds its block of collected data to the
blockchain which is sent to it. We can see that both UAV 2
and UAV 3 receive block from UAV 1 in the purple and green
blockchain respectively. Now both of these blockchains reach
UAV 5 at different time instants and contain the block added
by UAV 1. So UAV 5 can check whether the block added by
UAV 1 is same in the both the blockchains and hence in that
way it can check the validity and security of the routes 1-2-5
and 1-3-4-5 through which the blockchains have come to it.
This reduces the vulnerability of the blockchain to obstacles
in line of sight which may corrupt the data and makes it more
immune to cyber-physical attacks.
1 2
1 3
1 3
Now, UAV 5 can check the authencity of
data coming from UAV 2, UAV 3 and UAV 4
by comparingthe content of block 1 in
the purple and green blockchains.
UAV 1 receives blue
blockchain from another
UAV and creates two new
blockchains, purple and
green with its own block.
UAV 2 receives purple
blockchain from UAV 1 and
adds its own block to it.
UAV 3 receives blue and green
blockchains from UAV 1 and adds its
own block to the green blockchain.
UAV 4 receives green
blockchain from UAV
3 and adds its own
block to it.
UAV 5 receives blue blockchain
from UAV 3, purple blockchain
from UAV 2 and green
blockchain from UAV 4. Thus,
the propagation continues.....
Fig. 14: Double-block checking mechanism in a UAV network
based on the model proposed in [24]. It makes it more immune
to physical obstacles in line of sight and cyber physical attacks.
4) Dynamic imaging of large areas: With the help of
blockchain, the UAVs system can be empowered to image
large areas just like a satellite but from a lower height.
Blockchain helps in the collection of the data from different
UAVs and their collective processing at ground data centers. In
[24], the authors present such an application wherein a large
UAV network, each UAV shares its local view in the form of
the block on the blockchain as shown in Fig. 14. Finally, these
blockchain reach the ground station and data centers where
the global view is made. Also as discussed in the previous
section such a network is robust against obstacles blocking
line of sight and cyber-physical attacks which makes it more
reliable. This view can be shared with Air Traffic Control
(ATC) authorities, UAV operators, etc., to implement Collision
Avoidance Algorithms and plan their flight routes accordingly.
5) Create an efficient and secure data transmission mecha-
nism: All the UAVs which are to participate in the surveillance
can be registered in the network before the fleet starts the
surveillance activity. Hence the Public keys of all the UAVs
will be available with everyone in the fleet and can be used
for signing the message securely to everyone. This avoids the
MiM attack as the message encrypted by a public key can be
decrypted by a corresponding private key which are private to
the individual UAVs.
C. Challenges
1) Latency: The distribution of information in such UAV
networks is slow as each UAV share the data with UAVs that
are close enough to communicate when possible and the next
UAV does the same thing and in this way the information is
propagated in the whole network. So although such medium
of communication is reliable it leads to a lot of latency which
may be fatal as the intruder may have caused considerable
damage in that time.
2) Limited memory and power: Surveillance applications
require a large amount of data collection especially if the area
to be monitored is large. So in these cases the size of the
blockchain may be very large which can be difficult for UAVs
with limited onboard resources to store and process.
A. Motivation
Edge computing is a very happening technological domain
in the market today because of the latency and cost issues with
big cloud servers [196].There have been also some studies to
decrease the latency and optimize edge cloud-lets [197], [198].
Physical proximity to the connected devices ensures low jitter,
high bandwidth and also empowers the owner of the device to
enforce privacy policies via the edge server before the data is
released to the cloud. One of its interesting features is mobile
edge computing (MEC) which offers services to users via near-
site mobile devices like UAVs. UAV networks can play an
important role in the implementation of MEC especially during
emergencies such as disasters when the stationary ground
infrastructure is not available. Also, MEC is seen as one of
the key technologies towards 5G [199] and hence considerable
developments are required to make it ultra-reliable in terms
of survivability, availability ad connectivity. This is where
blockchain can be used. Blockchain can enable the participant
UAVs to maintain a high trust among themselves and help
achieve a flat architecture. Here, we discuss a model of
a neural blockchain for achieving an ultra-reliable caching
scheme in Edge-UAV networks [200].
B. Role of blockchain
Blockchain can be used for increasing the reliability of MEC
communications using UAV caching, in terms of connectivity,
availability, and survivability. In the model proposed by [200],
the authors suggest using a neural network on a combination
of three blockchains to generate an optimal master blockchain-
based on which the optimal path for the UAVs is decided. They
also present a detailed mathematical approach for calculating
the reliability of the system as a parameter. If the calculated
reliability parameter is not in the theoretical optimal range,
the iterations in the neural network can be increased to
arrive at the optimal blockchain. Also, blockchain facilitates
content sharing and data delivery between the user equipment
connected to the edge servers and the caching servers with
the help of its smart contracts and transaction models. One of
its main utilities is to support caching based on page ranks,
which is derived with the help of survivability of page requests
coming from different user equipment. In the experiments
carried by [200] it was demonstrated that using blockchain the
probability of connectivity reaches 0.99, survivability becomes
greater than 0.90, energy consumption is decreased by 60.34
percent and the reliability reaches 1.0 even for a large number
of users. Thus blockchain as a technology can be used to make
MEC communications ultra-reliable.
C. Challenges
Implementing blockchain for reducing the maintenance,
cost, and administration of MEC services and for the iden-
tification of appropriate servers requires several issues to be
resolved. Some of them identified by [200] are related to
lower and upper bounds on memory for blockchain-enabled
communication, survivability of UAVs with excessive compu-
tations, failure analysis, server dominance, and sharing and
content identification. These challenges need to be addressed
before such an application can be rolled out in the market.
Some solutions in this direction can be found in literature.
[201] discusses the importance of partitioning and offloading
in smart mobile devices. Also, [202] discusses the method
of adaptive partitioning for distributed optimization of mobile
applications. So, such measures need to be adopted to make
blockchain-based UAV networks suitable for MEC applica-
As the number of UAVs grow over time, several challenges
regarding their management and security will need to be
addressed. Blockchain as a tool can be useful in tackling these
as discussed in the previous sections. But certain applications
may require additional tools that will enhance the application
of blockchain in UAV networks. Also, blockchain can enhance
the role of other technologies in UAV applications and has
the potential to enhance the applicability of UAV systems in
a wide variety of practical scenarios such as military and
commercial establishments, environment monitoring, traffic
management, etc. Based on the detailed study done in the
previous sections of this paper, we present a summary of the
role of blockchain in different application scenarios of UAV
systems in Table II. However, there are more possibilities to
explore this exciting synergy of UAVs and blockchain. Thus,
a broader perspective is required as to how blockchain-based
UAV networks can influence different application scenarios
and how other technologies can contribute to or benefit from
it. We present here a discussion on the same.
A. Artificial intelligence-driven blockchain solution for UAVs
An application of Artificial intelligence (AI) in blockchain-
based UAV networks was already discussed in section VIII
where a neural network was applied on three different
blockchains to create an optimized blockchain which gives
the optimal fly routes for the UAVs [200]. Another state of
the art application of AI is being done by the Deep Aero
project [203] where it is used to build a smart, autonomous
self-governing system for UAVs with many blockchain-based
practical applications. It is a blockchain-based framework for
air traffic management of UAVs. Whenever we talk about
UAVs, we usually talk about an aerial vehicle operating
without any human. The absence of humans might decrease the
operational cost, but it also comes with several disadvantages
such as the risk of collision with other UAVs, destruction of
public property and much more. A framework is necessary
which could guide on-field UAVs by providing them a set of
regulations and maps so that mishaps can be avoided. The
specific utilities which the project highlights are as under.
1) Air traffic management: Air traffic management for
manned vehicles is a completely human, manual and compar-
atively easy process, but air traffic management for unmanned
vehicles is a highly complex system. UAVs fly in low-altitude
zone, so they need a complex set of data and programs to
help them monitor the environment around them as well as to
make communication with other manned/unmanned vehicles
in immediate proximity to escape any potential collision. Deep
Aero’s UTM (UAV traffic management) platform comes into
effect here. UTM is the infrastructure that allows a UAV to ex-
change information such as its location coordinates with other
aerial vehicles (manned/unmanned), air space management
services, airport personnel, and air traffic control. Ongoing
research is exploring various prototype technologies such as
airspace design, dynamic geofencing, congestion management
to make the UTM platform highly effective and fool-proof.
2) Deep chain UAV identity system: UAVs do not carry a
specific identity in the real environment, thus, it becomes very
difficult to provide a specific set of instructions to a UAV. This
necessitates an identity management system that is addressed
by the Deep Aero Project. Deep chain UAV registration is a
blockchain-based registration system that provides a unique
identity to UAVs, and even pilots so that a specific set of
instructions can be sent to specific UAVs/pilots.
B. Blockchain driven explainable AI (XAI) based UAV systems
1) Brief introduction to XAI: Explainable Artificial intel-
ligence (XAI) aims at making AI systems more explainable.
Present-day machine learning technology which is core to AI
applications is very opaque, nonintuitive and is not compre-
hensible by common users [204]. Analysts find it difficult to
find out the reasons behind failures, successes and prevent pre-
viously occurred errors and suggest corrective measures. XAI
addresses this problem by making more explainable models
and at the same time maintain a high learning performance.
2) blockchain-based XAI UAV systems: Blockchain ensures
a high level of trust by maintaining the data intact in a trans-
parent ledger and can be used to make the decision making
process explainable for systems operating in a multi-agent en-
vironment where trust on the decisions can enhance the speed
of operations. In [205], the authors discuss a few scenarios
TABLE II: Role of blockchain in enhancing the utility of UAV systems.
Utility Role of blockchain Utility Role of blockchain
UAV systems for
automation of
supply chain
Automating data storage and
Security of UAV networks
Mitigating jamming of UAV
Automating transactions
Detecting UAV hijacks, poi-
soned data and ensuring data
Automating decision making Avoiding mid-air collisions of
UAV services
Creating new business models Securing UAV communications
Collision free movement of
UAVs Securing UAV data types
Uniform load sharing Securing data dissemination
Data and entity authentication
UAV surveillance
Maintaining high trust of in-
truder alarm detection
Cooperation and fast synchro-
Securing the surveillance data
from adversaries
Decentralized storage
in UAV networks
Enable mutually beneficial
transactions between
heterogeneous IoT agents
Reduce system vulnerability
to cyber physical attacks and
physical obstacles
Dynamic imaging of large areas
Increasing air data security Create an efficient and secure
data transmission mechanism
Tackle the problem of limited
storage and processing power
onboard UAVs
UAV networks for
edge computing
Increasing reliability of Mobile
Edge Computing (MEC) net-
works in terms of connectivity,
availability and survivability
where this can be applied such as cloud computing, smart
cities, and user satisfaction management. The combination of
these three state-of-the-art technologies, namely blockchain,
XAI, and UAVs can be used in applications where there are
limited resources (e.g., UAV systems can be deployed to detect
fire in a particular locality). As soon as an alarm is raised by
a particular UAV, a nearby fire station is informed and the
rescue team reaches the location following the coordinates
of the UAV. There is a possibility of false alarms in such
cases which poses a big challenge for the fire fighting team as
there are limited resources to be deployed and all the alarms
cannot be addressed. In such cases, XAI implemented using
blockchain can be a more reliable option which the common
users can trust as compared to just using AI to predict the
truthfulness of a system. Blockchain can maintain a history
of alarms transparently raised by UAVs. Based on this data
the truthfulness of each UAV can be calculated using XAI
algorithms, thus making the system explainable. The alarm
raised by the most trustworthy UAV is considered a priority.
The importance of maintaining a high trust level of alarms is
also discussed in [204].
C. IoT inspired blockchain-based UAV delivery systems
UAV systems possess the advantage of enjoying the shortest
route to destinations by following an almost straight path
route via low altitude air corridors as compared to road
transportation which is constrained by traffic and the way
roadways are constructed. Hence, many delivery companies
are looking towards developing UAV delivery systems for
direct delivery to consumers in a fast and secure manner.
UAVs are also safer than conventional delivery systems as
they will not act maliciously and tamper the packages which
may happen in case of manual delivery systems.
1) Chronicled: A new application area in this domain is the
door-to-door package delivery system where the UAV can drop
or handover the package via the consumer’s door or window.
Chronicled, a company working on blockchains is trying a
similar implementation of UAV delivery system using IoT
[206]. The consumers’ houses may have IoT enabled doors
and windows and the UAVs can interact with them via the
Internet. A blockchain stores data regarding the identity of
UAVs to ensure that only authentic UAVs are allowed entry
through the doors and windows. Whenever an order is placed,
a UAV arrives near the house with the package and sends
request to the door or a window through which it is supposed
to enter the house, the chip on the IoT enabled door/window
checks if the UAV is authentic by referring to the blockchain
and if its identity is verified, it opens to let the UAV enter the
2) Walmart: Walmart is aiming to utilize blockchains to
develop a smarter package delivery and tracking system [207].
The U.S. Patent and Trademark Office issued a new patent on
Walmart’s name recently. It explains a smart package delivered
via UAVs which includes a device to store the information
regarding a blockchain-related to the environmental locations,
the content of the package, manufacturer, location, model
number, etc. The blockchain component is planned to be
encrypted into the device and will contain "key addresses
along the chain of the packages custody, including hashing
with a seller private key address, a courier private key address,
and a buyer private key address" [208]. Thus this is another
major step in the application of blockchain in package delivery
systems. There have been other efforts also by some other
big players such as Amazon which is developing Amazon
Sir prime since 2013 and Dorado, a blockchain company that
launched an ICO in May 2018 to develop a UAV delivery
system [206].
D. Blockchain inspired UAV systems for the security industry
UAVs have a huge scope of application in the security
industry. We had discussed its surveillance potential in section
VII which is relevant for monitoring purposes and can be used
in securing sensitive locations. Alternatively, UAVs also have
the potential to act as the next generation of robotic guards and
can shield the target from both air and ground attacks. Using
blockchain, such an application can be coordinated and man-
aged transparently from remote locations. Also, monitoring air
space security is a major concern today. Last year an incident
at Gatwick airport, London highlighted the need for this [206].
In December 2018, many flights were grounded during busy
hours due to the spotting of unidentified UAVs near the
commercial runways. Due to this, over 1,000 flights were
grounded which affected the holiday plans of over 140,000
people leading to a huge monetary loss. One of the carriers,
Easy jet lost around 19 million dollars [206]. This highlights
the need to register UAVs in a common platform such as
blockchain to trace and prevent the source of such attacks.
Although this incident did not result in any casualties, the
authorities initially did fear the possibility of terrorist attacks.
Such uncertainties can be used by adversaries to exploit the
system in the future. A possible solution for this can come
from IBM. The company filed a patent in 2017 highlighting
how a permissioned blockchain can be integrated with UAVs
to provide airspace controllers with the information regarding
UAVs and their operators and thus ensuring air-space security.
E. Blockchain and UAV based solution for environment con-
This is one of the most exciting areas where blockchain
empowered UAV systems can be deployed to track poaching
activities and animal movements. UAV systems can easily
operate in dense forest environments and thus have the po-
tential to make a difference in this field. Across Africa,
many national parks are employing UAVs to combat poaching
activities [206]. Also, mapping of river surfaces and oceans
over a large area can help monitor algae count and check
the health of water bodies. Soar, a company operating out of
Australia aims to work on aerial photography via UAV systems
to improve urban planning, smart agriculture, natural resource
management, and disaster relief [206]. People interested in
such data have to conventionally depend on search engines
such as Google to provide them with mapping technology. But
with the rise of new companies such as Soar, static mapping
is no longer the only option. The public can get hold of
dynamic mapping capabilities by exchanging data over the
blockchain. The contributors will be credited and compensated
for the contributions leading to a competitive incentive based
decentralized data exchange platform.
Based on the above discussion, we summarize the different
application areas on integrating UAVs and blockchain in Table
III giving the application scenario, the problem addressed and
the proposed solution for each area. In Table IV, we summa-
rize the implementation details discussed in each application
area based on the available works in the literature and briefly
compare them with standard available solutions which do not
make use of blockchain.
A. Challenges
UAVs and blockchain as individual technologies have some
challenges which limit their capabilities and also impact their
combined applications. Based on our study we try to present
some of the major issues which may be roadblocks to their
practical applications.
1) Privacy issues: UAVs can be used to monitor the personal
property of the public against their wish and knowledge.
Such applications of UAVs are possible and there has to
be strict regulation to tackle these. Blockchain as a tech-
nology can further the efficiency of UAV applications, but
if the total number of UAVs hovering in the sky goes up,
people’s privacy may be at a risk. A detailed discussion
of the societal impact of UAVs is also presented in [209].
2) Air traffic violation: With the increasing number of UAVs
in the airspace, there is a need to have a proper civil
air traffic management system in place for coordination
between the UAVs. As discussed in section IX an incident
at Gatwick airport resulted in a lot of chaos and monetary
loss because of unknown UAVs being spotted near the
airport airspace [206]. Such incidents can become more
frequent if the civil aviation authorities do not integrate
robust air space management systems for UAVs. Until
such precautions are taken, expanding the use of UAVs
by incorporating technologies such as blockchain will be
a questionable task.
3) Limited onboard resources for UAVs: To execute consen-
sus algorithms of blockchain, miners require considerable
processing power. Incorporating this onboard the UAVs
can be a challenging task. This is a common problem
which all blockchain-based UAV systems may face in the
future. UAVs already have complex payloads to carry in
addition to their battery and flying mechanism system. In
addition to that, if they have to play the role of nodes in
a blockchain, considerable processing power and storage
capabilities will also need to be incorporated into their
4) Quantum attacks: With the advent of quantum computing,
blockchains need to be secured against quantum attacks
since quantum computers have very powerful processing
capabilities that may provide the adversaries sufficient
resources to execute 51 percent attacks in the future.
There have been some studies related to this issue such as
TABLE III: Summary of blockchain applications in UAV systems.
Application scenario Problem addressed Proposed solution Ref.
Supply chain automation
The tedious task of inventory management
done by humans is prone to delays and
A blockchain-based inventory management sys-
tem where UAVs scan products with RFID tags
and send information to a blockchain which vali-
dates it and ensures transparency. Smart contracts
are used to carry out transactions with third
Need for a secure communication chan-
nel between UAVs participating in various
steps in a multi-agent system designed for
commercial purposes.
Blockchain used as a secure communication
channel between UAVs via its public and private
key mechanism. [175]
Providing coordinated
UAV services
Need for a global channel for commu-
nication and storage in UAV networks
deployed in applications such as disaster
relief, security, network relaying etc.
Blockchain used as a global communication plat-
form where UAVs can digitally sign and send
encoded data. It also empowers the UAVs in the
network to take decisions in a democratic way by
accepting inputs from other UAV members.
Need to have inter-service operation
capabilities between different network
providers to cater to the areas having ultra
high density of users. Also ensuring trust
between the service providers who may be
competitors in the market.
Blockchain-based trust agreement between the
vendors to provide inter-service operations where
each UAV acts as a node in the blockchain. The
record of services of each vendor is maintained
in the blockchain in a transparent way, ensuring
trust mutual trust.
Providing decentralized
storage in UAV networks
Limited storage and processing power on-
board the UAVs operating as part of In-
dustrial IoT networks which require heavy
data storage and processing capabilities.
A blockchain empowered decentralized storage
mechanism where UAVs acting as air sensors
transmit their data to ground sensors and in
return pay the ground sensors with rewards via
blockchain for their storage and processing ser-
Security of UAV
Named data networking (NDN) is being
actively explored for UAV adhoc networks
for better speed and security. However,
features of NDN make them highly vul-
nerable to content poisoning, i.e., injection
of fabricated or corrupted content into the
An NDN based UAV Network with a permis-
sioned blockchain to securely verify and record
data. An efficient consensus algorithm is em-
ployed to provide services in a decentralized
manner to detect inside attackers.
Need to have autonomous UAV systems
for mitigating network jamming attacks,
electromagnetic weapons and other possi-
ble adversaries.
A blockchain-based UAV network where each
UAV has a copy of the on-board blockchain.
UAVs can refer to blockchain data for deciding
their fly routes and action plan, in case of jam-
ming of command signals from control stations
or from other UAVs in the network.
In commercial applications, UAV net-
works face the challenge of securely send-
ing data to end users and also maintaining
confidentiality of the data.
Use Ethereum-based public blockchain for secur-
ing data collection and transmission in an Internet
of drone environment. It ensures data integrity,
accountability, authorization and confidentiality.
UAV swarm based
surveillance network
Operation of UAV networks in urban areas
is challenging because of blocking of line
of sight (LoS) due to obstacles in the
urban environment.
A blockchain-based UAV traffic information ex-
change network to securely transmit traffic data.
Via blockchain a double block checking mech-
anism can be implemented which makes the
system immune to cyber threats and obstacles in
UAV networks used for surveillance ap-
plications face many security challenges
because of their dynamic topology.
Use a security approach based on principles of
blockchain which can detect suspicious events in
the surveillance data and also detect malicious
UAVs via a distributed trust management policy.
UAV networks for
edge computing
Lack of focus on ensuring ultra reliable
communication facilities in Mobile Edge
Computing (MEC) applications.
A blockchain and neural network based ap-
proach which uses UAVs as on-demand nodes
for caching purposes to provide ultra-reliability. [200]
TABLE IV: Implementation, effectiveness, and comparison of the solutions discussed in this study.
Application scenario Implementation details Effectiveness of the solution /
comparison with other solutions
Supply chain automation
A blockchain-based inventory management
system was tested in [173] with a practi-
cal UAV implementation for scanning RFID
tagged products in an inventory setup.
The implemented system was found to be
faster compared to conventional human-
based inventory management systems, as
discussed in [173].
Providing decentralized
storage in UAV networks
Authors in [187] carried out simulations using
their proposed mathematical model for the
decentralized storage system.
Simulation results in [187] show that the
trading consensus process can be usefully
adopted in the air-to-ground industrial IoT
system; the optimized active density could
maximize the QoS for AS (Air sensors)
and increase the transmission rate for the
information exchange system.
Security of UAV networks
Simulations were conducted in [191] for eval-
uating a permissioned blockchain system with
an efficient and scalable consensus algorithm
for securing ICN based UAV adhoc networks.
Simulation results in [191] showed that
the proposed system has lower sys-
tem overhead and achieves better latency
performance than Internet Key binding
In [192], authors conducted security evalua-
tion of their work in terms of communication
cost and time and compared it with state-of-
the-art works.
Results in [192] show that the proposed
scheme is better compared to other state-
of-the-art schemes in terms of cost and
UAV swarm based
surveillance network
In [25], the proposed model for security
of UAVs used for surveillance was tested
in a novel agent based simulator, ABS-
The experimental results showed that
around 90% of UAVs were able to cor-
roborate information about a person walk-
ing in a controlled area, while none of
the UAVs corroborated fake information
coming from a hijacked UAV.
In [24], the authors carried out Monte Carlo
simulations to characterize the performance
of the system proposed by them in a highly
dynamic traffic environment.
The results in [24] showed that the UAV-
TIEN system proposed by them can in-
crease the traffic data broadcasting range
and reduce the fraction of missing UAVs
in a city.
UAV networks for
edge computing
In [200], the authors carried out simulations
for evaluating the performance of their net-
work model in terms of flyby time, probability
of connectivity, energy consumption, failure
rate, survivability, reliability, and area spectral
The findings of the study demonstrated
the utility of the proposed system for a
large set of users in different altitudes and
different number of drones.
[210]–[214]. This issue can prove to be a major challenge
in the area of securing blockchain-based applications in
the future.
5) Machine learning (ML) and algorithmic game-theory
based attacks: Blockchain-based applications are also
vulnerable to majority attacks executed using ML and
algorithmic game-theory approach. This is one of the
current challenges that the blockchain community needs
to address to make it more secure [215], [216].
B. Future research directions
Integration of both the technologies, UAVs and blockchain
is an exciting field of research today. There has been some
effort in this direction and much more can be done. We discuss
a few possible research directions here which can have a great
impact based on our study.
1) Simulation software for blockchain-based UAV systems:
Implementation of blockchain in UAV systems is a com-
plex system integration problem and it requires rigorous
testing before it can be rolled out in the market. The
same problem is also discussed in [190]. There have
been few studies that have used agent-based simulation
software for similar applications such as in [25]. A
more dedicated platform incorporating features of both
blockchain technology and UAVs is required.
2) Protecting private/permissioned blockchain systems
against intelligent attacks: Most blockchain-based UAV
applications and applications in fields other than financial
markets require a private/permissioned blockchain. Such
blockchain networks are more vulnerable to attacks as
compared to public blockchains where the number of
participants is very high and it is very difficult to execute
a majority attack on them. Also with an increase in more
advanced types of attacks such as quantum attacks, ML
and game-theory based attacks on blockchain networks,
there is an increasing need for securing the blockchain.
Research in this direction is required to make private
blockchain networks more immutable and safer.
3) Optimising UAV power consumption and increasing their
fly-time: Due to the limited battery capacity of UAVs,
their fly-time is usually very less. Thus, for increasing
their fly-time there is a need to optimize UAV operations.
Blockchain-based applications require more processing
power, thus power consumption can be a crucial bot-
tleneck. There have been some studies in this direction
such as [147], [217], [218], but more research is required
before we arrive at a practical solution.
In this study, we reviewed various applications of
blockchain in UAV systems. UAV systems are very dynamic
and sophisticated in nature. Using blockchain features such
as smart contracts and consensus mechanism, they can be
automated and secured. The increasing deployment of UAVs
in the airspace has led to a need for secure and reliable UAV
communications, as we have seen in applications such as in-
ventory management, air traffic system and semi-autonomous
delivery systems. This paper also provided an outlook of
secure UAV systems for coordinated operation capability in
scenarios where different players in the market collaborate to
provide solutions to users in an efficient way by making use of
the blockchain principles and its features. By using blockchain
technology, commercial houses can share the same set of
UAVs as it ensures trust and transparency. Various security
and privacy threats on UAVs were identified and potential
blockchain-based solutions to mitigate these threats were also
suggested. We also discussed the challenges involved in each
application that need to be addressed. Overall, blockchain as
a technology helps in overcoming many problems such as
coordination, security, collision avoidance, privacy, decision
making, signal jamming, etc. faced by UAV systems. We
also suggested some future research directions for blockchain-
based UAV systems. The application scenarios discussed in
this paper hold immense potential for real-life implementation
in both military and commercial domains.
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... Blockchain can aid in preventing such attacks through blockchain consensus algorithms where any UAV can report suspicious activity. If the number of entries contradicting a UAV is greater than a certain threshold that UAV is said to be malicious [96]. ...
... Blockchain can encrypt data and store it within the blockchain such that the data cannot be accessed by anyone without the correct decryption key. Additionally, blockchain can protect the four main data types in a UAV network (UAV identifier, flight route control, sensor data and flying schedule) by writing and updating them within a blockchain block [96]. c) Disadvantages: As discussed in the security section (Section III-D3a), it should be noted that the distribution of data/data processing on several edge nodes has the disadvantage of increased potential attack surface. ...
... Also, edge AI allows for federated learning and blockchain which can improve security and privacy. For example, blockchain can encrypt data within the blockchain such that it is only accessible to someone with a decryption key [34] [96]. ...
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The latest 5G mobile networks have enabled many exciting Internet of Things (IoT) applications that employ Un-manned Aerial Vehicles (UAVs/drones). The success of most UAV-based IoT applications is heavily dependent on artificial intelligence (AI) technologies, for instance, computer vision and path planning. These AI methods must process data and provide decisions while ensuring low latency and low energy consumption. However, the existing cloud-based AI paradigm finds it difficult to meet these strict UAV requirements. Edge AI, which runs AI on-device or on edge servers close to users, can be suitable for improving UAV-based IoT services. This paper provides a comprehensive analysis of the impact of edge AI on key UAV technical aspects (i.e., autonomous navigation, formation control, power management, security and privacy, computer vision, and communication) and applications (i.e., delivery systems, civil infrastructure inspection, precision agriculture, search and rescue operations, acting as aerial wireless BSs and drone light shows). As guidance for researchers and practitioners, the paper also explores UAV-based edge AI implementation challenges, lessons learned, and future research directions.
... Blockchain is a new technology that is rapidly gaining traction in fields such as finance [32], UAVs [33]- [36], IoT [37]- [40], smart cities [41], [42], smart grids [40], supply chain management [43], VANETs [44], [45], and many others. It was originally proposed by S. Nakamoto in his whitepaper [46] on Bitcoin. ...
... For example, it is very difficult to accurately model the randomness that is inherent in vehicular network topologies, even using stochastic mechanisms. Therefore, the research community would be well aided by the development of better simulation tools and prototype tested frameworks [33]. ...
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Vehicular networks promise features such as traffic management, route scheduling, data exchange, entertainment, and much more. With any large-scale technological integration comes the challenge of providing security. Blockchain technology has been a popular choice of many studies for making the vehicular network more secure. Its characteristics meet some of the essential security requirements such as decentralization, transparency, tamper-proof nature, and public audit. This study catalogues some of the notable efforts in this direction over the last few years. We analyze around 75 blockchain-based security schemes for vehicular networks from an application, security, and blockchain perspective. The application perspective focuses on various applications which use secure blockchain-based vehicular networks such as transportation, parking, data sharing/ trading, and resource sharing. The security perspective focuses on security requirements and attacks. The blockchain perspective focuses on blockchain platforms, blockchain types, and consensus mechanisms used in blockchain implementation. We also compile the popular simulation tools used for simulating blockchain and for simulating vehicular networks. Additionally, to give the readers a broader perspective of the research area, we discuss the role of various state-of-the-art emerging technologies in blockchain-based vehicular networks. Lastly, we summarize the survey by listing out some common challenges and the future research directions in this field.
... The use of drones in applications that are related to a complex and harsh environment depending on the tasks, whether military or civilian, makes them face several challenges. The most important of which is the possibility of cooperation between them, and the mechanism of planning and following the best path to complete their tasks [5], 6]. Traditional drone path planning methods have weak practical characteristics because they rarely take into account the limitations of obstacles and heights. ...
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Recently, Drones and UAV research were becoming one of the interest topics for academia and industry, where it has been extensively addressed in the literature back the few years. Path planning of drones in an area with complex terrain or unknown environment and restricted by some obstacles is one of the most problems facing the operation of drones. The problem of path planning is not only limited to searching for an appropriate path from the starting point to the destination but also related to how to choose an ideal path among all available paths and provide a mechanism for collision avoidance. By considering how to construct the best path, several related issues need to be taken into account, that relate to safety, obstacle avoidance, response speed to overtake obstacles, etc. Swarm optimization algorithms have been used to provide intelligent modeling for drone path planning and enable to build the best path for each drone. This is done according to the planning and coordination dimensions among the swarm members. In this paper, we have discussed the features and characteristics of different swarm optimization algorithms such as ant colony optimization (ACO), fruit fly optimization algorithm (FOA), artificial bee colony (ABC), and particle swarm optimization (PSO). In addition, the paper provides a comprehensive summary related to the most important studies on drone path planning algorithms. We focused on analyzing the impact of the swarm algorithm and its performance in drone path planning. For that, the paper presented one of the most used algorithms and its models employed to improve the trajectory of drones that rely on swarm intelligence and its impact on the optimal path cost of drones. The results of performance analysis for the ACO algorithm in a 3D and 2D-dimensional environment are illustrated and discussed, and then the performance evaluation of the ACO is compared to the enhanced ACO algorithm. The proposed algorithm achieves fast convergence, accelerating the process of path planning.
... But, due to increased risk failure, manual configuration, and higher maintenance costs, the industries shifted towards the wireless infrastructure, such as 3G, 4G, 5G, and 6G [26]. Nowadays, the 6G communication network is highly preferred in industrial automation due to numerous advantages [48,49], such as high data availability, minimum network delay, improved network performance, maximum spectral efficiency, ubiquitous connectivity, etc. [50,51,52,53,54]. For real-time applications in industrial automation, 6G network is the most suitable and feasible. ...
Automation of industrial tasks has become a necessity for organizations due to the high risks and low operational efficiency of traditional procedures. The Industrial Internet-of-things (IIoT) has proved a reality with ubiquitous computing, which interconnects tens of billions of objects for real-time data transfer, such as devices and machines. However, the rapid increase in connected devices and machines leads to various security issues, such as data modification, sniffing, and many more. Achieving secure and reliable communication between devices becomes challenging as the entire communication takes place over an open channel, i.e., the Internet. Most of the security solutions presented in the literature are centralized and susceptible to security, latency, reliability, and single-point-of-failure issues. Blockchain is a plausible solution to mitigate the aforementioned issues with reduced capital and operating expenditures, whereas a sixth-generation (6G) network makes communication faster and more reliable. Motivated by these facts, this paper presents an exhaustive survey on blockchain-based industrial automation in the 6G environment. Also, a blockchain and 6G-enabled industrial automation architecture for secure and efficient communication among IIoT devices are proposed. This paper also presents a case study on blockchain-based additive manufacturing for designing three-dimensional products to validate the proposed architecture. The performance of the proposed case study is evaluated based on network parameters such as delay and packet loss. Finally, various research challenges and future directions are suggested in this emerging area.
... Keeping in view of these facts, the authors in [23] presented blockchain, as a distributed ledger, which uses cryptographic methods to secure the shared data. It can also be used to ensure the accuracy of the data stored, as well as to improve the reliability and accountability of unmanned areal vehicles (UAVs). ...
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With increase in the use of contactless deliveries during the times such as COVID-19 pandemic, the emphasis was to minimize the human presence to reduce the spread of virus. In this regard, drones are one promising alternative to be used as delivery agents. However, security and Quality of Service (QoS) are major concerns while making use of drones for deliveries. In order to secure the drone communication system, we propose, CovaDel: a blockchain-based scheme to secure data transactions for the drone delivery use case that works in a phased manner. The proposed scheme make use of decoupled blockchain architecture to overcome the limited resources capabilities of drones to perform blockchain-based computations. Further, to ensure the QoS adherence, we also propose a QoS-aware communication approach that handles collisions and congestion on the basis of firefly algorithm’s attractiveness parameter (light intensity) received by the drones. Results obtained using a simulated environment verify the efficacy of the proposed scheme on the basis of gas consumed, transaction time, average network throughput, and delay.
Globalization and developments in technology have contributed to the growth of numerous industries around the globe which are creating major impacts on today's supply chains. The supply chain has drastically changed under the open-ended influence of globalization. The need for different types of mobilities is increasing due to urbanization and population growth, rapid development in the E-commerce industry, and the growing expectation of customers. Crowd logistics is one of these techniques that is gaining rapid attention in the logistics industries and many start-ups have started using this method in their business models. This paper has investigated the crowd logistics and the challenges like user trust, data safety and security, security of the financial transactions for both the customer and the crowd and tracking service quality. Using the Blockchain technology, an e-commerce crowd logistics conceptual model is proposed. Moreover, through different scenarios the capabilities of the proposed model besides the detailed flow of the business processes have been discussed. The conceptual model of a Blockchain-based crowd logistics has used the functionalities of Blockchain such as the smart contracts and the DApps and especially has increased the flexibility of the crowd logistics system.
Blockchain technology is the “fifth evolution” in the era of computing. The characteristics of blockchain such as immutability, tamper-proof, decentralized, private, and permissioned blockchain have attracted the world's attention. This paper briefs about the core concepts of blockchain, smart contracts, and architecture behind the integration of IoT devices and blockchain. The proposed architecture using the blockchain and Inter Planetary File System (IPFS) improves the way of storing, handling, and sharing medical data and records. A comprehensive study on blockchain-based smart applications across diverse sectors such as financial, manufacturing, supply chain, healthcare sectors is also included in this paper. Finally, the paper also enumerates challenges, limitations, and future trends in the area of blockchain.
Unmanned aerial vehicles (UAVs) have significant prospects in a plethora of public and civic spheres. Recently, UAVs have focused primarily on applications where human presence is either impossible or hazardous. A swarm of small UAVs can cooperatively complete operations more proficiently and economically than a single large UAV. However, many issues must be resolved before stable and reliable multi-UAV networks can be realized. Task assignment in fleets of UAVs is concerned with cooperative decision-making and control. UAVs possess various functional abilities and kinematic constraints while carrying limited resources onboard. UAVs are nominated to execute multiple sequential tasks supportively on numerous ground targets. The prime objective of task assignment is to minimalize the task accomplishment time and UAV energy consumption. To date, several task assignment algorithms have been designed for UAV networks, and they are comprehensively surveyed in this paper in terms of their main ideas, operational features, advantages, and limitations. These task assignment algorithms are then compared in terms of their significant characteristics and performance factors. To the best of the authors' knowledge, no survey on task assignment techniques for different UAV missions currently exists in the literature. We also discuss open issues and challenges and then suggest projections for task assignment algorithms concerning possible future directions.
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UAVs are being widely deployed in security and surveillance applications around the world. Due to deployment in remote environments and also due to limited resources on these devices, they are susceptible to device capture and physical tampering attacks. This heightens the risk of sensitive data stored in the UAVs to be captured by adversaries. To address this issue, a two-stage lightweight mutual authentication protocol is presented in this paper, well suited to SDN-backed multi UAV networks deployed in surveillance areas. Formal security proof of the protocol is presented to highlight its security features. We also compare our protocol with other state-of-the-art works in terms of computation latency and resilience against known security attacks.
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Use of Unmanned Aerial Vehicles (UAVs) is rapidly increasing in various domains such as disaster management, delivery of goods, surveillance, military, etc. Significant issues in the expansion of UAV-based applications are the security of (IoT to UAV) communication, and the limited flight time of the UAVs and IoT devices considering the limited battery power. Standalone UAVs are not capable of accomplishing several tasks, and therefore swarm of UAVs is being explored. Security issues in the swarm of UAVs do not allow the applications to leverage the full benefits that one can offer. Several recent studies have proposed the use of a distributed network of UAVs to upgrade the level of security in the swarm of UAVs. In this paper, a framework for secure and reliable energy trading among UAVs and charging stations is presented. Advanced blockchain, based on the tangle data structure is used to create a distributed network of UAVs and charging stations. The proposed model allows the UAVs to buy energy from the charging station in exchange for tokens. If the UAV does not have sufficient tokens to buy the energy, then the model allows the UAV to borrow tokens from the charging station. The borrowed tokens can be repaid back to the charging station with interest or late fees. A game-theoretic model is used for deciding the buying strategy of energy for UAVs. Numerical analysis shows that the proposed model helps in providing increased utility for the swarm of UAVs and charging stations in a secure and cost-optimal way as compared to the conventional schemes. The results can eventually be applied to IoT devices that constantly need energy to perform under ideal conditions.
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Data sharing and content offloading among vehicles is an imperative part of the Internet of Vehicles (IoV). A peer-to-peer connection among vehicles in a distributed manner is a highly promising solution for fast communication among vehicles. To ensure security and data tracking, existing studies use blockchain as a solution. The blockchain-enabled Internet of Vehicles (BIoV) requires high computation power for the miners to mine the blocks and let the chain grow. Over and above, the blockchain consensus is probabilistic and the block generated today can be eventually declared as a fork and can be pruned from the chain. This reduces the overall efficiency of the protocol because the correct work done initially is eventually not used if it becomes a fork. To address these challenges, in this paper, we propose a Directed Acyclic Graph enabled IoV (DAGIoV) framework. We make use of a tangle data structure where each node acts as a miner and eventually the network achieves consensus among the nodes. A game-theoretic approach is used to model the interactions between the vehicles providing and consuming offloading services. The proposed model is proven to be highly scalable and well suited for micro transactions or frequent data transfer among the nodes in the vehicular network.
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The emergence of mobile cloud computing enables mobile users to offload computation tasks to other resource‐rich mobile devices to reduce energy consumption and enhance performance. A direct peer‐to‐peer connection among mobile devices to offload computation tasks can be a highly promising solution to provide a fast mechanism, especially for deadline‐sensitive offloading tasks. The generic blockchain‐based system might fail in such a scenario due to it being a heavyweight mechanism requiring high power consumption in the mining process. To address these issues, in this article, we propose a directed acyclic graph‐enabled mobile offloading (DAGMO) algorithm. DAGMO model is empowered by traditional blockchain features and provides additional advantages to overcome the fundamental limitations of generic blockchain. A game‐theoretic approach is used to model the interactions between mobile devices. The numerical analysis proves the proposed model to enhance the overall welfare of the participating nodes in terms of computation cost and time.
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The Vehicle-to-Grid (V2G) network is, where the battery-powered vehicles provide energy to the power grid, is highly emerging. A robust, scalable, and cost-optimal mechanism that can support the increasing number of transactions in a V2G network is required. Existing studies use traditional blockchain as to achieve this requirement. Blockchain-enabled V2G networks require a high computation power and are not suitable for microtransactions due to the mining reward being higher than the transaction value itself. Moreover, the transaction throughput in the generic blockchain is too low to support the increasing number of frequent transactions in V2G networks. To address these challenges, in this paper, a lightweight blockchain-based protocol called Directed Acyclic Graph-based V2G network (DV2G) is proposed. Here blockchain refers to any Distributed Ledger Technology (DLT) and not just the bitcoin chain of blocks. A tangle data structure is used to record the transactions in the network in a secure and scalable manner. A game theory model is used to perform negotiation between the grid and vehicles at an optimized cost. The proposed model does not require the heavy computation associated to the addition of the transactions to the data structure and does not require any fees to post the transaction. The proposed model is shown to be highly scalable and supports the micro-transactions required in V2G networks.
With rapid technological advancements within the domain of Internet of Things (IoT), strong trends have emerged which indicate rapid growth in the number of smart devices connected to IoT networks and this growth cannot be supported by traditional cloud computing platforms. In response to the high volume of data being transferred over these networks, the edge and fog computing paradigms have emerged. These paradigms are extremely viable frameworks that shift computational and storage resources from the centralized cloud servers to distributed LAN resources and powerful embedded devices at the edge of the network. These computing paradigms, therefore, have the potential to support massive IoT networks of the future and have fueled the advancement of IoT systems within industrial settings, leading to the creation of the Industrial Internet of Things (IIoT). IIoT is revolutionizing industrial processes in a variety of domains. In this chapter, we elaborate on the impact and viability of edge and fog computing paradigms in IIoT through a use-case approach. Finally, we conclude with the future research directions like security and privacy for edge and fog computing in IIoT, relevance of Blockchain for IIoT, programmability and task partitioning, virtualization, etc.