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A Futuristic Blockchain based Vehicular Network Architecture and Trust Management System


Abstract and Figures

In a complex network of smart vehicles, some issues arise related to security, privacy, selfishness of nodes and node failures. We have proposed an architecture of vehicular network in a smart city based on blockchain. Some scenarios and design principles are also provided. Contrary to prior architectures of vehicular networks, our proposed model provides robustness, scalability, adaptability, trust management as well as privacy and security. It eliminates the issue of selfish nodes and malicious nodes. Unlike other vehicular architectures,it also takes into account the passengers’ medical facilities and fault tolerance. In case of any failure of sensors or nodes,system will effectively tackle it. Both big data storage and fast computation are not possible on vehicles end. This can be handled by moving these processes to static nodes and data center. Malicious behaviour of nodes is handled using trust values and incentives mechanism in order to motivate nodes to work effectively while assigning penalty for selfish nodes.
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A Futuristic Blockchain based Vehicular Network
Architecture and Trust Management System
1st Usama Arshad
Department of Computer Science
COMSATS University Islamabad
Islamabad (44000), Pakistan
2nd Sakeena Javaid
Department of Computer Science
COMSATS University Islamabad
Islamabad (44000), Pakistan
3rd Sheeraz Ahmed
Department of Computer Science
Iqra National University
Peshawar, Pakistan
4th Beenish Seemab
Department of Computer Science
COMSATS University Islamabad
Islamabad (44000), Pakistan
5th Nadeem Javaid
Department of Computer Science
COMSATS University Islamabad
Islamabad (44000), Pakistan
Abstract—In a complex network of smart vehicles, some
issues arise related to security, privacy, selfishness of nodes
and node failures. We have proposed an architecture of
vehicular network in a smart city based on blockchain. Some
scenarios and design principles are also provided. Contrary to
prior architectures of vehicular networks, our proposed model
provides robustness, scalability, adaptability, trust management
as well as privacy and security. It eliminates the issue of selfish
nodes and malicious nodes. Unlike other vehicular architectures,
it also takes into account the passengers’ medical facilities and
fault tolerance. In case of any failure of sensors or nodes,
system will effectively tackle it. Both big data storage and
fast computation are not possible on vehicles end. This can be
handled by moving these processes to static nodes and data
center. Malicious behaviour of nodes is handled using trust
values and incentives mechanism in order to motivate nodes
to work effectively while assigning penalty for selfish nodes.
Index Terms—Blockchain, ITS, Electric Vehicles, Data
Center, Scalability, Privacy, Internet of Things.
EVs are getting smarter day by day. With the advancement
of Artificial Intelligence (AI) and Internet of Things (IoT)
devices; networks are getting faster and complex. Intelligent
Transport System (ITS) is also getting smart by using
the latest technology and devices to handle these vehicles.
Vehicles are using different sensors to detect on-going
processes around them. IoT advancements make it possible
to share data between different devices. This data can either
be processed by devices or sent to servers for processing.
Smart cities have developed efficient ITS over past years to
make vehicular networks and their communication faster and
secure. Traditional vehicular models lack smartness and are
not equipped with much sensors and devices. Normally, a
Global Positioning System (GPS) is present on traditional
vehicles to detect their location. However, in recent era due
to technological enhancements, now vehicular networks are
equipped with all types of sensors, radars and IoT devices to
increase the throughput [1]. Vehicles have on-board resources
like sensors, computational resources, storage and Event
Data Recorder (EDR) [2]. Vehicular networks act as a
platform between vehicles to communicate faster. Vehicles
send messages to each other to tell each other about
traffic conditions, shortest paths to destinations,crowded
docking stations. Due to all this communication, vehicles
become aware of conditions and their overall performance
is increased [3].
In vehicular network, every node is unknown of
authenticity of other nodes and this creates lack of trust
between them. In some cases, vehicles send wrong messages
to other vehicles about traffic conditions, destinations and
docking stations that lead to malicious behavior. This can
be handled by using a trust management system. However,
in vehicular network, it is difficult for a single entity to do
this. Another way is providing some incentive mechanism for
vehicles [4]. Road Side Units (RSUs) are used to store big
data and to execute high computations because vehicles have
limited resources. It can also be used for trust management
[5]. The concept of blockchain based incentive mechanism
based on data storage for wireless sensor networks is
described in [6]. Nodes get incentives based on data stored
by them; as the data increases the incentive also increases,
respectively. Any incentive technique can be used to provoke
nodes to act properly in a network. This reduces selfish nodes
and malicious nodes when we use penalties; this issue is
almost eradicated. In vehicular networks, processing should
be faster as vehicles have to communicate in seconds to
produce responses [7]. Moreover, network should be robust
and secure. In case, if a vehicle is far from controller
node then this can lead to a failure of the system. The
concept of trust factor is also introduced in [8]. A trust
978-1-7281-4452-8/19/$31.00©2019 IEEE
factor is generated for each vehicle in the form of Intelligent
Vehicle Trust Points (IVTP). These trust points help to
check the trust factor of a particular vehicle. Our system
is closely related to this approach. Blockchain technology
can be used to effectively handle above-mentioned issues.
It provides the possibilities of secure network with efficient
trust management and node-to-node communication. Due
to its unique characteristics, it is used in wide range of
fields. Proposed system effectively handles issues related to
trust management by using decentralized controller nodes,
ratings are done directly by vehicles, and trust profiles are
stored on controller nodes. Incentive mechanism makes it
possible to detect and remove malicious or selfish nodes
from network. In case, if a vehicle is far from controller
node and it cannot request services, then it can send request
to nearby miner node which is in range of controller node
to forward its request. Our proposed architecture is closely
related to this architecture as proposed in [9]. However, the
work in [9] is limited to architecture and design principles.
Our model covers the broader scope of smart city dealing
with trust management, repairing of failures and health care
too. Our proposed model is closely related to the trust
mechanism as proposed in [10]. Ratings are generated by
vehicles which are sent to RSUs (which are in our proposed
model represented as controller nodes). Controller nodes are
managed by authority in our proposed model and data is
stored on a blockchain.
IoT industry is evolving and IoTs are used in different
fields. Services provided from servers sometimes can
be malicious and dangerous for devices; however, much
mechanisms available before are only for devices with high
computational power and resources. Consensus mechanism
also greatly affect the model and Proof of Authority
(PoA) consensus with consortium blockchain is normally
used with IoT devices for working efficiently. In [16],
authors have proposed a blockchain based model to ensure
security of users against insecure services provided by edge
service providers. Permissioned blockchain is used with
PoA consensus mechanism. Off-chain service verification
and identification is done. Latency can be an issue in
case of large networks. In future, reputation system can be
formed for service providers according to feedback from
devices/lightweight clients. Blockchain works effectively in
case of IoT devices and provides peer-to-peer access in
a network where two entities can directly interact with
each other without involving any third party. Blockchain
is powerful and can revolutionize different industries. A
new algorithm is developed in [18] for access control. This
work also proposed Conventional Neural Network (CNN)
architecture for Channel State Information (CSI) predictions
by using two blockchains: one is fraud chain that stores
the fraud CSI users while other is the integrity chain.
Blockchain consensus based device-to-device network is used
to authenticate CSI and is matched with the predicted CSI
by CNN. After making consensus from nodes authenticity of
CSI, it is also checked with a CNN by matching both outputs
from consensus and on basis of resultant data, CNN then
enters into the blockchain. If authentication is successful,
data is entered in I-Chain or integrity Chain; while in case
of failure of authentication, CSI data is entered into F-Chain
or fraud Chain (which means a user is using fake identity).
System is limited in terms of scalability, as we have to
use many CNNs to check data on a large scale, which
will increase cost and computational resources. Moreover,
in this scenario, it is only limited to scenario where users are
cooperative and cannot refuse to accept the network access.
Internet commerce is flourishing; however, it has its weakness
in terms of old traditional business models. E-business model
completely changed approach of old methods. Blockchain is
one of trustworthy technologies to solve many issues related
to privacy, security and trust effectively. Third party plays
an important role in traditional business models but it has
its own drawbacks starting from high costs to consuming
more human resources. Traditional models provided a cost
centric approach, which should be replaced by value-based
models for IoT. Blockchain based models provide a trustless
environment by removing the third party. Moreover, it
ensures the security and privacy. The work in [19] introduced
DAC (Distributed Autonomous Corporation), and proposed
an IoT e-business model. They have discussed the four
stages: pre-transaction stage, preparation stage, negotiation
stage and contract-signing stage. Two commodities are
addressed including paid data and smart property. In future,
this model can be implemented on large scale introducing
Near Feild Communication (NFC) modules and Application
Programming Interfaces (APIs) for users to interact with
ease. A new blockchain based access control architecture
is described in [20], where all access and permissions
are considered global on blockchain. There can be many
networks and management hubs. System is compared in
terms of scalability and it produces good results in case of
multiple management hubs. However, does not cope with
existing systems with single management hub. System is
limited to some scenarios in terms of performance.
IoT is an emerging field with technological advancements,
we also need better systems to manage them. Internet
commerce is flourishing; however, it has weaknesses in
terms of old traditional business models. Blockchain is one
of trustworthy technologies to solve many issues related
to privacy, security and trust effectively. Third party plays
an important role in traditional business models; however,
it has its own drawbacks starting from high costs to
consuming more human resources. Another issue is to
handle big data of blockchain as each node has to store
data of blockchain, which is increasing day by day. The
applied Network Coded Distributed Storage (NCDS) is used
to solve storage issues in [25]. Proposed model provides
low complexity as compared to prior models and provide
two methods, one for deterministic and other for rate-less
approach. In deterministic approach, each node keep record
of one encoded packet. In rate-less, Reduced Echelon Form
(REF) and Backward Substitution are combined to produce
binary feild random shift encoding. The proposed system
in [26], first divides the data into parts (packets) and then
encodes each part. The packets store on different nodes.
The stored packets can create complexities when data size
increases. Moreover, in blockchain, data is on all nodes so
hackers must be able to hack atleast 51% nodes; however,
in this case, he may need to hack only some nodes to
get a particular data. In future work, we can propose some
consensus mechanism to tackle this issue. Cloud computing
is used for IoT devices on a large scale for getting data
from cloud servers directly or using cloud services which
create long delays. As a solution, edge computing and edge
devices are used for providing low latency to users. In [26],
authors deployed a blockchain (green blockchain) for data
sharing at edges. Edges collaborate with each other to share
the data. Proof of collaboration (PoC) is used to decrease
computational resources. Proposed off-loading module is
used to reduce storage consumption due to blockchain. With
the advancement in technologies, many complexities also
arise. When different mobile network operators work together
in an environment. After the 5th generation (5g) network,
heterogeneity of networks is increased. When different
networks work; each of them have some barriers and these
barriers may cause issues. A blockchain based data sharing
system is proposed in [27] with two blockchains; one for
storing behavior record and other for storing data. Different
mobile network operators are competitors in a market and
their joining may damage the economic growth. Therefore,
it may be difficult to persuade them to join. In future, we
will implement the model on different data sharing scenarios.
Research is done to increase knowledge all over the World.
However, this data is intellectual property of authors and
normally third parties manage this data and provide access to
others, where authors have no access to directly check who
is accessing their data. So, there should be proper policy of
reusing research data and this data should only be reused
after the consent of real owner of data.
We have proposed a blockchain based vehicular network
architecture in a smart city and have provided solutions for
different problems of vehicular network, which meet future
requirements and challenges. Proposed model is applicable
on a large scale effectively. In proposed architecture, all
nodes are interconnected and are divided into 3 types: (1).
Controller nodes, (2). Miner nodes and (3). Ordinary nodes.
Controller nodes are static nodes and are less in number. The
function of controller node is to provide services/responses
to nodes asking for it. Controller nodes are connected to an
authority/datacenter and these nodes create trust profiles in
their blockchain and store trust values of each vehicle in it
based on ratings sent by other vehicles (miner nodes and
ordinary nodes). If rating is positive, one is incremented in
trust profile of that vehicle and if rating is negative, one
is decremented from profile. If a vehicle is getting negative
rating continuously that means it is a malicious node so its
trust values will keep on decrementing until they reach 0 or
-1 after that it will be removed from network by authority.
Miner nodes are vehicles that can handle requests from
ordinary nodes and other miner nodes. They forward requests
of ordinary nodes to controller nodes. They have sensing
devices, data storage and computing resources. Ordinary
nodes are vehicles requesting services from other nodes.
Their first priority is to send request to controller node for
services; however, if they are not in range of signal, they send
this request to closest miner node and then it forwards this
request to controller node. Authority decides which nodes act
as miner nodes and this authority also acts as a data center.
Figure 1 shows detailed overview of level 1 of basic proposed
architecture in which nodes are interconnected. Nodes send
messages to each other and ratings are generated for those
messages. These ratings are then sent to controller nodes to
store them in trust profiles of these nodes. Authority overall
controls which node act as a miner node. Miner node has
ability to forward requests.
A. Privacy and Security
All connections and data sharing between nodes is secured
using private to public key encryption as shown in Figure 2.
Ordinary nodes encrypt data with their private key and send
it to miner nodes or controller nodes and public keys which
decrypt that data.
B. Incentive Mechanism for Miner Nodes
When nodes communicate with each other, every message
received is rated and this rating is sent to controller nodes.
Based on this rating from vehicles/nodes, controller nodes
create trust profiles in blockchain for each node. Miner nodes
are forwarding nodes in this network and they may act as
selfish nodes. In order to solve this problem, we proposed
an incentive mechanism which depends on the trust profiles
incentives and are given to top 5% miner nodes with highest
trust values. However, 5% miner nodes with lowest trust
values will also have to pay some penalty. Figure 3 shows
incentive mechanism for miner nodes.
C. Medical Facilities and Fault Repairing
In case of any failure, either of sensors or on-board devices,
nodes can request immediate assistance from authority.
Requests are sent by controller nodes to authority and
authority communicates further to send immediate help.
Similarly, in case of medical emergency, request is sent to
Fig. 1: Blockchain based Vehicular Network architecture.
Fig. 2: Information sharing between nodes.
authority and it communicates with medical center to send
help or reroute the vehicle towards medical center. Healthcare
is limited only if the vehicle rider meet an accident or
some health issues during the ride. Figure 4 shows our final
proposed model including medical and repairing facilities.
Simulations are done on Windows 10 operating system
and coding is done in solidity while using Remix for its
execution. Metamask is used as a wallet for accounts. Ganach
is used to provide fake accounts for experimentation. Remix
Fig. 3: Incentive Mechanism for miner nodes
Fig. 4: Final Proposed model
also provides fake accounts with 100 fake ether each for
experimentation. Matlab and Microsoft Excel are used for
graphical representation of results.
A. Scalability and Performance
Number of controller nodes and miner nodes greatly affect
the scalability with respect to number of ordinary nodes.
The scalability of the system is inversely proportional to
the performance of the network considering node failures;
however, those failed nodes will be repaired sooner and
performance will not decrease much. Execution cost and
transaction cost are used as performance parameters for
displaying plots of increasing cost with respect to number
of nodes increasing in the network. Graphical representation
in Figure 5 represents that increasing scalability or number
of nodes in network also increases overall network cost.
The transactional cost for a single transaction between two
vehicles is 110831 while the executional cost for this single
task is 86295.
Fig. 5: Total nodes in network with respect to total cost.
B. Forwarding Nodes/ Miner nodes
If a node sends message to a message to controller
node and that node is far away from controller node then
some other nodes closer to it will forward this message
to controller nodes. Each sending will have a transaction
cost and execution cost. The transaction cost is computed
as below: Total cost = No. of nodes as forwarding nodes
1) Transaction cost: Transaction cost required in
forwarding message from vehicle to controller nodes. When
a vehicle sends request to controller nodes, this request
is forwarded by some forwarding nodes/miner nodes.
These miner nodes have their own transaction cost for
each transaction. Therefore, overall transaction cost for
communication between ordinary node and controller node
depends upon number of farwarding nodes as shown in
Figure 6.
2) Executional Cost: Executional Cost is computed for
forwarding message from vehicle to controller nodes. The
Transaction cost for forwarding single message is 24331.
Fig. 6: Forwarding nodes and their transaction cost.
When forwarding nodes increase, the cost also increases
with each transaction as shown in Figure 7. The Execution
cost for forwarding single message is 1011. When number
of forwarding nodes increase, the cost of the system also
increases for each transaction.
Fig. 7: Forwarding nodes and their execution cost.
3) Time: If we consider time taken for one transaction
between two nodes as one minute. This time taken depends
upon the number of forwarding nodes just like in case of
cost. As the forwarding nodes increase, total time taken also
increases. This means that if single transaction takes one
minute, two transactions will take two minutes and if we
have ten nodes in scenario; we will have nine transactions
and the total time taken will be nine minutes which is also
shown in Figure 8.
1) Case 1: Unique ID: An unique id is allotted to each
vehicle. This unique id is the identity of vehicle in the
network. This id holds all the information about vehicle and
can be used to get all information of the vehicle. If this id is
compromised; then anyone can know the identity of vehicle.
Fig. 8: Time taken in transaction with number of nodes.
This issue can be solved by changing the id randomly after
some time in the network.
2) Case 2: Redundancy of IDs: To remove redundancy of
vehicular ids, we can divide this id into two parts. First part
is fixed part given by authority, it is a unique id. On the other
hand, second part is generated randomly after some random
time. This completely solves issue of redundancy and privacy
3) Case 3: Patient Record: Another issue is to have
control over patient’s data. Three entities are involved: (1).
authority, (2). patient and (3). medical centers or hospitals.
None of above entities should have full control over this
data. Authority should have only access to prescribed medical
facilities, so it should be able to contact them in emergency.
Patients should be able to see all records and should not be
able to edit any record as a patient does not know about
medical terms and procedures. Records can only be edited
by doctors and doctors are permitted by patients.
We have proposed and implemented a blockchain based
vehicular network architecture in a smart city which meets
future requirements and challenges. This system can be
implemented on a large scale, where vehicles are registered
directly by authority and can communicate with each other
through encryption. Scalability, adaptability and robustness
can be achieved by using appropriate number of nodes
which are visualized through simulations. Scalability is
achieved upto satisfactory level using appropriate number
of forwarding and ordinary nodes. Privacy and security
can also be achieved by using latest techniques of hashing
and encryption. Controller nodes generate trust profiles for
vehicles in a blockchain after getting feedback rating from
nodes. In case of controller node malfunctions, data would
remain unaffected on the blockchain. Authority is also acting
as data center.
Passenger’s safety is also ensured, if sensors detect any
fatal health issues, node sends a signal to authority. Moreover,
it also takes into account fault tolerance and fault repairing.
In case of any failure of sensors, nearest node gets signal
message which forwards it to controller node and then
immediate help is sent to it. Trust values are generated based
on ratings from nodes. Incentives are be given to nodes which
act properly for a fixed time and penalty is also applied
for selfishness of nodes. Authority removes nodes which act
as malicious or selfish in network. System scalability and
performance are discussed and analyzed. Both scalability and
performance depend upon number of particular nodes in the
In future, we will present the complete implementation of
this model. Our current proposed system has limitations in
terms of high cost and more resource usage in some scenarios
like maximum number of forwarding nodes, which can be
handled by using an algorithm to find shortest path between
controller node and ordinary node.
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... Blockchain based vehicular network architecture and trust management system is proposed. [45] Ethereum and Remix are used to represent node activities and performance. ...
... In our recent work [45], we proposed a blockchain based vehicular network architecture that was scalable, robust, and adaptable by using vehicular network architecture similar to proposed in [46] with a rating system similar to proposed in [47] to handle malicious nodes. However, after achieving scalability, vehicular network architecture lost its cost-effectiveness and executive effectiveness. ...
... Blockchain based vehicular network architectures have been proposed in [45], [47], which provide scalability, robustness and can handle malicious nodes. However, using blockchain in this type of network scenario imposes a high computational cost and is timeconsuming. ...
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... The analysis based on different trust-based blockchain approaches for IoV security is elaborated as follows: Arshad and Javaid designed the vehicular network architecture using blockchain for the smart city. 113 This approach was introduced to eliminate problems related to the malicious nodes and selfish nodes. In this scenario, the malicious behavior of the nodes was handled based on the incentive mechanism and trust values. ...
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Recently, The Internet of Vehicles (IoV) concept is becoming very popular due to sharing of the data between vehicles and the infrastructure. The sharing of data is very important for enhancing vehicular services, but at the same time makes IoV vulnerable for security and privacy issues. The smart and interconnected vehicles produce sophisticated services for transport authorities, car manufacturers, vehicle owners, and other service providers. IoV are very vulnerable to malicious attacks due to its self-organizing nature and the open source nature of its implementations. This exposes the smart and interconnected vehicles to a variety of privacy and security threats, such as a remote hijacking or location tracking of vehicles. Thus, the security for IoV environment is critical. Blockchain technology has been recently used for cybersecurity due to the robustness and integrity preserving nature of its design. This review article provides a detailed survey of existing work in the literature to secure IoV through blockchain techniques such as security, privacy, reputation, distributed, decentralized , data sharing, authentication, and trust-based approaches. The paper presents the detailed discussion and analysis of these blockchain techniques to secure IoV. In addition, we present the gaps and research challenges identified from the existing research works. This provides work directions for future research in blockchain techniques to secure IoV.
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The transformation of conventional grid into Smart Grid (SG) requires strategic implementation of the demand-sensitive programs while considering the varying fluctuations in the consumers’ load. The core challenges faced by existing electric system are that how to utilize electrical devices, how to tackle large amount of data generated by end devices and how to meet energy demands of consumers in limited resources. This dissertation is focused on the energy management of residential sector in the SG. For this purpose, we have proposed the Energy Management Controllers (EMCs) at three levels: at home level (including the single and multiple homes), at building level and at regional level. In addition, cloud and fog based environments are integrated to provide on-demand services according to the consumers’ demands and are used to tackle the problems in existing electric system. At first level, heuristic algorithms based EMC is developed for the energy management of single and multiple homes in residential sector. Five heuristic algorithms: genetic algorithm, binary particle swarm optimization algorithm, bacterial foraging optimization algorithm, wind driven optimization algorithm and our proposed hybrid genetic wind driven algorithm are used to develop the EMC. These algorithms are used for scheduling of the residential load during peak and off peak hours in a real time pricing environment for minimizing both the electricity cost and peak to average ratio while maximizing the user comfort. In addition, the advancements in the electrical system, smart meters and implementation of Renewable Energy Sources (RESs) have yielded extensive changes to the current power grid for meeting the consumers’ demand. For integrating RESs and Energy Storage System (ESS) in existing EMCs, we have proposed another Home EMC (HEMC) that manages the residential sector’s load. The proposed HEMC is developed using the earliglow algorithm for electricity cost reduction. At second level, a fuzzy logic based approach is proposed and implemented for the hot and cold regions of the world using the world-wide adaptive thermostat for the residential buildings. Results show that the proposed approach achieves a maximum energy savings of 6.5% as compared to the earlier techniques. In addition, two EMCs: binary particle swarm optimization fuzzy mamdani and binary particle swarm optimization fuzzy sugeno are proposed for energy management of daily and seasonally used appliances. The comfort evaluation of these loads is also performed using the Fanger’s Predicted Mean Vote method. For increasing the system automation and on-demand availability of the resources, we have proposed a cloud-fog-based model for intelligent resource management in SG for multiple regions at next level. To implement this model, we have proposed a new hybrid approach of Ant Colony Optimization (ACO) and artificial bee colony known as Hybrid Artificial Bee ACO (HABACO). Moreover, a new Cloud to Fog to Consumer (C2F2C) based framework is also proposed for efficiently managing the resources in the residential buildings. C2F2C is a three layered framework having cloud, fog and consumer layers, which are used for the efficient resource management in six regions of the world. In order to efficiently manage the computation of the large amount of data of the residential consumers, we have also proposed and implemented the deep neuro-fuzzy optimizer. The simulation results of the proposed techniques show that they have outperformed the previous techniques in terms of energy consumption, user comfort, peak to average ratio and cost optimization in the residential sector.
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Crowd sensing is a perception mode that recruits mobile device users to complete tasks such as data collection and cloud computing. For the cloud computing platform, crowd sensing can not only enable users to collaborate to complete large-scale awareness tasks but also provide users for types, social attributes, and other information for the cloud platform. In order to improve the effectiveness of crowd sensing, many incentive mechanisms have been proposed. Common incentives are monetary reward, entertainment & gamification, social relation, and virtual credit. However, there are rare incentives based on privacy protection basically. In this paper, we proposed a mixed incentive mechanism which combined privacy protection and virtual credit called a blockchain-based location privacy protection incentive mechanism in crowd sensing networks. Its network structure can be divided into three parts which are intelligence crowd sensing networks, confusion mechanism, and blockchain. We conducted the experiments in the campus environment and the results shows that the incentive mechanism proposed in this paper has the efficacious effect in stimulating user participation.
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The emerging network computing technologies have significantly extended the abilities of the resource-constrained IoT devices through the network-based service sharing techniques. However, such a flexible and scalable service provisioning paradigm brings increased security risks to terminals due to the untrustworthy exogenous service codes loading from the open network. Many existing security approaches are unsuitable for IoT environments due to the high difficulty of maintenance or the dependencies upon extra resources like specific hardware. Fortunately, the rise of blockchain technology has facilitated the development of service sharing methods and, at the same time, it appears a viable solution to numerous security problems. In this paper, we propose a novel blockchain-based secure service provisioning mechanism for protecting lightweight clients from insecure services in network computing scenarios. We introduce the blockchain to maintain all the validity states of the off-chain services and edge service providers for the IoT terminals to help them get rid of untrusted or discarded services through provider identification and service verification. In addition, we take advantage of smart contracts which can be triggered by the lightweight clients to help them check the validities of service providers and service codes according to the on-chain transactions, thereby reducing the direct overhead on the IoT devices. Moreover, the adoptions of the consortium blockchain and the proof of authority consensus mechanism also help to achieve a high throughput. The theoretical security analysis and evaluation results show that our approach helps the lightweight clients get rid of untrusted edge service providers and insecure services effectively with acceptable latency and affordable costs.
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The rise of the Internet of Things (IoT) implies new technical challenges such as managing a universally vast number of IoT devices. Despite the fact that there are already a variety of secure management frameworks for IoT, they are based on centralized models, which limits their applicability in scenarios with a large number of IoT devices. In order to overcome those limitations, we have developed a distributed IoT management system based on blockchain. In this paper, we compare the performance of our solution with the existing access management solutions in IoT. We study the delays and the throughput rate associated with the systems and analyze different configurations of our solution to maximize its scalability. The objective of the paper is to find out whether our solution can scale as well as the existing management systems in IoT.
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Vehicular edge computing (VEC) is introduced to extend computing capacity to vehicular network edge recently. With the advent of VEC, service providers directly host services in close proximity of mobile vehicles for great improvements. As a result, a new networking paradigm, vehicular edge networks is emerged along with the development of VEC. However, it is necessary to address security issues for facilitating VEC well. In this paper, we focus on reputation management to ensure security protection and improve network efficiency in the implementation of VEC. A Distributed REputAtion Management System (DREAMS) is proposed wherein VEC servers are adopted to execute local reputation management tasks for vehicles. This system has remarkable features for improving overall performance: i) distributed reputation maintenance, ii) trusted reputation manifestation, iii) accurate reputation update, and iv) available reputation usage. In particular, we utilize multi-weighted subjective logic for accurate reputation update in DREAMS. To enrich reputation usage in DREAMS, service providers optimize resource allocation in computation offloading by considering reputation of vehicles. Numerical results indicate that DREAMS has great advantages in optimizing misbehavior detection and improving recognition rate of misbehaving vehicles. Meanwhile, we demonstrate the effectiveness of our reputation-based resource allocation algorithm.
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Nowadays, the development of traditional business models become more and more mature that people use them to guide various kinds of E-business activities. Internet of things (IoT), being an innovative revolution over the Internet, becomes a new platform for E-business. However, old business models could hardly fit for the E-business on the IoT. In this article, we 1) propose an IoT E-business model, which is specially designed for the IoT E-business; 2) redesign many elements in traditional E-business models; 3) realize the transaction of smart property and paid data on the IoT with the help of P2P trade based on the Blockchain and smart contract. We also experiment our design and make a comprehensive discuss.
A device-to-device (D2D) underlaying cellular network is pervasive to support various wireless applications. However, due to the dramatic increase of data transmission in the network with limited amount of wireless resource, a few users may be required to temporarily disconnect from the network to avoid the interruption of data transmission in the whole network. A critical issue of determining the user access in D2D underlaying networks is the authenticity of channel state information (CSI), and usually a user with a higher CSI can be allocated a larger amount of wireless resource or have a higher probability of staying in the network. In this paper, we propose a blockchain consensus based scheme to verify the authenticity of CSI, and add the users who intentionally advocate a higher value of CSI into a fraud chain. Also we consider both the cross-tier interference (CTI) caused by a mobile user and the presence of a user in the fraud chain to determine the access of a user. The analysis results show that our proposed user access scheme can enhance the network performance by efficiently controlling the use access in mobile applications.
The rapid growth of Internet of Vehicles (IoV) has brought huge challenges for large data storage, intelligent management, and information security for the entire system. The traditional centralized management approach for IoV faces the difficulty in dealing with real time response. The blockchain, as an effective technology for decentralized distributed storage and security management, has already showed great advantages in its application of Bitcoin. In this paper, we investigate how the blockchain technology could be extended to the application of vehicle networking, especially with the consideration of the distributed and secure storage of big data. We define several types of nodes such as vehicle and roadside for vehicle networks and form several sub-blockchain networks. In the paper, we present a model of the outward transmission of vehicle blockchain data, and then give detail theoretical analysis and numerical results. Our study has shown the potential to guide the application of Blockchain for future vehicle networking.
Traditional centralized commerce on the Internet relies on trusted third parties to process electronic payments. It suffers from the weakness of the trust-based model. A pure decentralized mechanism called blockchain tackles the above problem and has become a hot research area. However, since each node in a blockchain system needs to store all transactions of the other nodes, as time continues, the storage room required to store the entire blockchain will be huge. Therefore, the current storage mechanism needs to be revised to cater to the rapidly increasing need for storage. Network coded (NC) distributed storage (DS) can significantly reduce the required storage room. This work proposes a NC-DS framework to store the blockchain and proposes corresponding solutions to apply NC-DS to blockchain systems. Analysis shows that the proposed scheme achieves significant improvement in saving storage room.
The Intelligent vehicle (IV) is experiencing revolutionary growth in research and industry, but it still suffers from many security vulnerabilities. Traditional security methods are incapable to provide secure IV communication. The major issues in IV communication, are trust, data accuracy and reliability of communication data in the communication channel. Blockchain technology works for the crypto currency, Bit-coin, which is recently used to build trust and reliability in peer-to-peer networks having similar topologies as IV Communication. In this paper, we are proposing, Intelligent Vehicle-Trust Point (IV-TP) mechanism for IV communication among IVs using Blockchain technology. The IVs communicated data provides security and reliability using our proposed IV-TP. Our IV-TP mechanism provides trustworthiness for vehicles behavior, and vehicles legal and illegal action. Our proposal presents a reward based system, an exchange of some IV-TP among IVs, during successful communication. For the data management of the IV-TP, we are using blockchain technology in the intelligent transportation system (ITS), which stores all IV-TP details of every vehicle and is accessed ubiquitously by IVs. In this paper, we evaluate our proposal with the help of intersection use case scenario for intelligent vehicles communication.
With the flourishing and advancement of the IoT, the smart city has become an emerging paradigm, consisting of ubiquitous sensing, heterogeneous network infrastructure, and intelligent information processing and control systems. A smart city can monitor the physical world in real time, and provide intelligent services to both local residents and travelers in terms of transportation, healthcare, environment, entertainment, and energy. However, security and privacy concerns arise, since smart city applications not only collect a wide range of privacy-sensitive information from people and their social circles, but also control city facilities and influence people’s lives. In this article, we investigate security and privacy in smart city applications. Specifically, we first introduce promising smart city applications and architecture. Then we discuss several security and privacy challenges in these applications. Some research efforts are subsequently presented to address these security and privacy challenges for intelligent healthcare, transportation, and smart energy. Finally, we point out some open issues for future research.