Conference PaperPDF Available

Blockchain based Authentication for end-nodes and efficient Cluster Head selection in Wireless Sensor Networks

Authors:

Abstract

In this paper, a secure blockchain based identity authentication for end-nodes is proposed in wireless sensor networks (WSNs). Moreover, to resolve the issue of limited energy in WSNs, a mechanism of cluster head (CH) selection is also proposed. The nodes in a network are authenticated on the basis of credentials to prevent from malicious activities. The malicious nodes harm the network by providing false data to nodes. Therefore, a blockchain is integrated with the WSN to make the network more secure as it allows only authenticated nodes to become a part of the network. Moreover in a WSN, sensor nodes collect the information and send it towards CH for further processing. The CH aggregates and processes the information; however, its energy depletes rapidly due to extra workload. Therefore, the CH is replaced with the node that has the highest residual energy among all nodes. The simulation result shows the network lifetime increases after CH replacement. Moreover, it shows that he transaction cost is very low during authentication phase.
Blockchain based Authentication for end-nodes and
efficient Cluster Head selection in Wireless Sensor
Networks
Sana Amjad1, Usman Aziz2, Muhammad Usman Gurmani1, Saba Awan1, Maimoona Bint E Sajid1, Nadeem Javaid1,
1Department of Computer Science, COMSATS University Islamabad, Islamabad 44000, Pakistan
2Department of Computer Science, COMSATS University Islamabad, Attock 43600, Pakistan
Email: Sanaamjad702@gmail.com, usmanaziz91@gmail.com,
usmankhangurmani@gmail.com, sabaawan046@gmail.com, maimoonasajid176@yahoo.com,
Correspondence: nadeemjavaidqau@gmail.com; www.njavaid.com
Abstract—In this paper, a secure blockchain based identity
authentication for end-nodes is proposed in wireless sensor
networks (WSNs). Moreover, to resolve the issue of limited energy
in WSNs, a mechanism of cluster head (CH) selection is also
proposed. The nodes in a network are authenticated on the
basis of credentials to prevent from malicious activities. The
malicious nodes harm the network by providing false data to
nodes. Therefore, a blockchain is integrated with the WSN to
make the network more secure as it allows only authenticated
nodes to become a part of the network. Moreover in a WSN,
sensor nodes collect the information and send it towards CH
for further processing. The CH aggregates and processes the
information; however, its energy depletes rapidly due to extra
workload. Therefore, the CH is replaced with the node that
has the highest residual energy among all nodes. The simulation
result shows the network lifetime increases after CH replacement.
Moreover, it shows that he transaction cost is very low during
authentication phase.
Index Terms—Blockchain, Wireless Sensor Networks, Identity
Authentication.
I. INTRODUCTION
The wireless sensor networks (WSNs) are useful in sensing
the environmental or physical changes in healthcare, surveil-
lance, transportation, etc. The sensors in WSN are randomly
deployed for environmental monitoring [1], [2]. The sensor
nodes have many constraints, which are limited battery, less
computation capabilities, low storage, etc., [3], [4].
Satoshi Nakamoto introduced blockchain in 2008 that has
emerged as a promising technology to address the issues of
data securitand remove dependency on the third party [5]. The
blockchain is used in the field of healthcare, energy trading,
smart grids etc. It gives a secure, decentralized, a distributed
mechanism for storage and addresses the single point of failure
issue. The blockchain provides a tamper-proof ledger in which
a new record is added after being validated by the miners. The
miner nodes validate the transactions by different consensus
mechanisms: proof of work (PoW), proof of authority (PoA),
proof of stack(PoS) etc., [6], [7]. In the PoW, all the interested
nodes participate and solve a mathematical puzzle. The node,
which solves the puzzle first is responsible for validating the
transaction and adding a block in the blockchain. This process
consumes a lot of computational power, which is not suitable
for energy constrained WSNs. Moreover, the blockchain uses
the smart contracts in which all the business rules are stored
and it removes the need of any external third party. In PoA,
only pre-selected nodes are responsible for mining, these nodes
are selected on the bases of their capabilities. Because, the
miners are pre-selected node; therefore, they do not have to
solve the mathematical puzzle that requires high computation.
Moreover, blockchain plays an important role in WSN and
provides security and privacy in them [8], [9]. It provides
security by detecting the malicious nodes in the network. There
are many techniques for malicious nodes detection [10], [11].
However, blockchain faces the issue of high storage cost which
is not suitable for WSN that are not resource enriched.
In the WSNs, sensor nodes gather data from the environ-
ment and forward it to CH for further processing. The CH
process the data and forward it to the base station (BS). The
nodes in the network are registered as well as authenticated
to prevent from malicious acts. In [12], CHs send the sensed
data to BS; however, there is no registration and authentication
mechanism for the network nodes. The malicious nodes can
enter into the network and make it vulnerable.
Whenever a node fails due to energy depletion in the
network, it affects the whole networks’ performance. There
is no mechanism in [13], [14] for the selection of CH. When
any CH fails to perform due to serve the network due to its
low energy, there is no criteria of selecting a new CH.
The list of contributions of this paper are as following:
nodes’ authentication is performed to prevent the network
from malicious activities,
a smart contract is used to resolve the trust issue by
removing third party, and
the CH is selected on the basis of nodes’ highest en-
ergy by using low-energy adaptive clustering hierarchy
(LEACH) protocol.
II. RE LATE D WO RK
In this section, relevant studies of blockchain in WSNs are
dicussed based upon limitations addressed.
A. Registration and authentication of nodes
The nodes in the IoT environment cooperate to provide the
services. However, in [6] and [14], nodes’ identity authenti-
cation is compromised, any node can enters in network and
behaves maliciously which affects the network performance.
The node identity authentication relies on the central authen-
tication server.
The sensors play an important part in IoT for different
purposes and one of them is nodes’ identity authentication.
However, sensors have very low computational power. In [13],
the authentication issue occurs because of non authenticated
nodes can enter in network and act maliciously. While in
[15], users’ privacy and authenticity need to be assured. As in
[16] the routing protocol is used to authenticate the devices;
however, the trust issue is created due to centralized authority.
In [17], the wireless body area network consists of sensors
that gather the data of human body parts and send it to the
local node publically. However, the nodes in the network are
not authenticated.
B. Storage issues in network nodes
In [18], the sensor nodes have some constraints such as low
storage and low computational power. Moreover, some nodes
in the network behave selfishly and do not store the data.
The PoW mechanism is used in previous work that consumes
much computational power. Whereas, in [19], a static routing
protocol is not good for the internet of underwater things
(IoUT) and there is a storage issue in the centralized system.
Also, in [20], PoW consensus is used. However, it consumes
high computational power and storage.
In addition to the problems discussed above, in [21], IoT
is integrated with the blockchain in a centralized manner and
PoW is used for the mining process. However, it creates central
point of failure due to central authority. In the network each
node stores data that is generated by other nodes. However,
the storage issue occurs. While in [22], the nodes data record
is stored in a centralized system that creates single point of
failure. Whereas in [23], blockchain is integrated with IoTs.
However, it is not suitable for keeping a copy of the ledger
due to storage constraints.
C. Data privacy of nodes
In [12], no mechanism is proposed for data protection due
to which any malicious node can steal data and harm the
network. Whereas in [24], the controlling and take care of
the manufacturing products in the industry are done by the
workers; however, data transparency issue occurs. The workers
can steal the restricted product information. Moreover, the
misuse of important records is another issue. Also, in [6], the
data security and privacy of sensor nodes are compromised in
the WSNs.
In [25], crowdsensing is essentially used to collect in-
formation using different devices. However, no data privacy
protection mechanism is used. As in [26], the dynamic WSNs
play an important role in collecting data; however, the un-
trusted behavior of nodes occurs. Whereas, in [15], users’
data privacy and authenticity need to be assured. Whereas
in [27], the information-centric network (ICN) is integrated
with a WSN. The caching data is duplicated and shared in the
network. However, data privacy and security concerns may
occur. While in [28], the concept of a smart city is developed
with the integration of IoT. However, due to data growth and
no management, data security issues occur. In [29], the data is
transmitted from sensor nodes to IoT devices; however, there
is no mechanism for data protection.
D. Excessive energy consumption
In [18], the sensing nodes in the network selfishly behave
and do not store the data. The PoW mechanism is used
in previous work that consumes much computational power.
Also, in [20], blockchain technology is used in different
fields for trading and supply chain purposes. PoW is used
as consensus mechanism that consumes high computational
power.
In [23], blockchain is integrated with IoT. However, IoT
nodes are less competitive and are not able to keep a copy
of the ledger due to low energy. Whereas, in [30], IOTA is
a distributed ledger that provides fast and tamper-proof infor-
mation. However, the ndes’ information gathering rate is very
low. The IoT sensors may have the very low computational
power and their energy may decreases very fast. It creates a
problem for IoT to validate the transactions very fast. While
in [31], sensor nodes do not have enough battery to survive
in the network and not able to communicate for a long time.
In [32], the wireless body area networks work evolutionary
with the healthcare applications. However, it consumes a lot
of energy consumption.
E. Malicious nodes detection and removal from networks
In a WSN, localization of sensor nodes is the major issue
nowadays. There are some nodes in the WSN, which give
the wrong location and act maliciously. In this way, network
security is compromised in [33]. Whereas, in [34], there is
no proper mechanism for the detection of malicious nodes.
Moreover, there is no traceability mechanism for the detection
of malicious nodes. Also, in [35], the industrial IoT (IIoT) is
being used in different fields such as manufacturing, health-
care. However, some service provisioning challenges occur. In
service provisioning challenges, the untrusted service provider
can act maliciously and provide the wrong services. On the
other side, the client can acts maliciously by repudiating
against the services.
In [18], the nodes in the network selfishly behave and do not
store the data. Whereas in [36], sensor nodes communicate by
finding the routing path. However, no best way is used to find
the malicious node and secure the data to be infected. While
in [37], the range based localization approach needs hardware
for finding the precise location and it becomes very costly.
Moreover, the range-free approach is affected by the malicious
nodes in the network. In [38], cloud based computing is
performed; however, data is retrieved through the internet and
no data security mechanism is performed.
F. Single point of failure issue due to centralized authority
In [14], nodes’ identity authentication is compromised,
which affects the network performance. The node identity
authentication relies on central authentication servers that are
considered third parties and cause single point of failure.
Whereas in [39], authors compare the centralized and dis-
tributed network model. In a centralized system, the data sent
to the cloud directly; however, data bandwidth and data latency
issues arise. In a distributed system, fog computing is used;
however, a single point of failure issue arises.
In [16], in the routing protocol, the central devices are used
to authenticate the devices; however, a trust issue is created
due to centralized authority. While in [22], shellfish products
are the most popular food throughout the globe. Its freshness
is needed for long time storage. Cold storage is needed for
maintaining its freshness. A WSN is a beneficial and great
impact on managing the cold operation. However, their records
are stored in a centralized system that creates single-point
failure and malicious attacks. In [40], the central authority
is used for data storage. However, single-point of failure issue
is created.
In the Table 1, the problems, their solutions and valida-
tion parameters are mentioned. For intrusion prevention of
malicious nodes, an authentication scheme is used. By using
authentication scheme, only authenticated nodes enter into the
network. The node battery issue resolved by selecting the
highest energy node using the LEACH protocol [41].
III. PROP OS ED S YS TE M MO DE L
In the proposed system model, a blockchain based model is
proposed for establishing the secure communication between
authentic nodes and CH.
Fig. 1: System model for end-nodes authentication and CH
selection
A. System components
The system model comprises of three primary entities: end-
nodes, CH and BS.
1) Sensor node:: In a WSN, the sensor nodes sense data
from the environment. These nodes are resource constrained
and not able to store the large amount of data. Therefore, they
send data to the CH for further computation and storage.
2) Cluster head:: The CH receives data from sensor nodes,
processes and stores it on BS. Our proposed model provides a
mechanism for the selection of CH on the basis of its residual
energy, when the battery of existing CH depletes. For this, the
energy of each sensor node in the network is calculated and
the node with highest residual energy is selected as cluster
head.
3) Base station:: The blockchain is deployed on BS, which
has sufficient resources for performing the validating trans-
actions. The BS stores sensing data and the credentials of
registered nodes. The CH then send data to BS for storage.
4) End-node:: Nodes’ registration and authentication
scheme is used to prevent network from malicious activities.
The authentication scheme use in this paper is motivated
by [14], the authentication scheme is used in this paper. In
the proposed system model, this scheme is used for private
blockchain. The unknown end-node sends a request to the
blockchain for registration. Initially, the blockchain checks
either this node is already registered in the network or not. If
end-node is already registered, then it will not be re-registered
in the network and proceed further otherwise, the blockchain
registers it. When any end-node wants some data from the
network, then it will authenticate firstly. The end-node is
authenticated on the bases of its credentials stored on the
blockchain at the time of registration. At the request time
the end-node provides its credentials, if these credentials are
same with the credentials stored on the blockchain, then it will
be considered as authenticated node. Otherwise, this specific
end-node will be announced as a malicious node and rapidly
removed from the network. After authentication, the end-user
is allowed to get the data from the network.
5) Smart contract:: A smart contract is a digital contract,
which is deployed on blockchain for handling the transactions
without the involvement of any third party. In this paper,
PoA consensus mechanism is used for nodes’ authentication
that consumes less computational power because pre selected
nodes perform mining process.
IV. SIMULATION RESULTS AND DISCUSSION
This section demonstrates the analysis of the proposed so-
lution. Fig. 2 depicts the message size during registration and
authentication phase. During registration, nodes send request
to enter in the network. The nodes send their credentials
for registration. Their credentials are stored in BS, whenever
end-node enters in the network first it is authenticated. The
authentication is performed by BS. The message size for
registration is high because much of the network resources
like bandwidth and throughput are used in sending the data to
the blockchain.
TABLE I: Mapping of problems to solutions and validations
Limitations Proposed Solutions Validations
L1. Nodes’ registration and authen-
tication [12].
L2. Malicious nodes detection [12]
S1. Authentication technique V1. Message size
V2. Transaction cost
L3. Node battery issue [13], [14] S2. LEACH protocol V3. Network lifetime
Registration phase Authentication phase
1
2
3
4
5
6
7
8
Message size (bytes)
Fig. 2: Registration and authentication message size for
end-nodes
First deadNode Tenth deadNodes All deadNodes
200
400
600
800
1000
1200
1400
Number of rounds
Fig. 3: Network lifetime
On the other hand, during authentication, less network re-
sources are used because BS has only to match the credentials
to verify end-nodes’ credentials. Only authenticated nodes take
part in the network. PoA consensus mechanism is used in our
proposed model to validate transactions. In this way, malicious
nodes are not allowed in the network to do malicious activities.
Fig. 3 illustrates the network lifetime and shows the number of
dead nodes based on number of rounds. There are 200 sensor
nodes and from these sesors, CH is selected on the basis of
highest residual energy. The energy of first CH depletes at
round No. 180. The energy of ten node depletes at round No.
200. The energy of all the nodes depletes at round No. 1200.
This shows that the network has good lifetime. The use of
LEACH protocol is to prolong the network lifetime and reduce
the energy consumption of nodes.
Registration phase Authentication phase
0
2
4
6
8
10
12
14
Transaction cost (gwei)
104
Fig. 4: Transaction cost
Fig. 4 illustrates the transaction cost of registration and au-
thentication of end-nodes. The transaction cost in registration
phase is greater than the authentication phase. Because during
registration phase, blockchain stores all the information of
nodes one by one to register end-nodes that takes much cost as
compared to authentication phase. During authentication phase
only the nodes have to authenticate from the information that is
already provided during registration phase. That is the reason
it does not take much time for authentication process.
V. CONCLUSION AND FUTURE WORK
The aim of this paper is to enhance the network lifetime
as well as to prevent it from malicious nodes. Therefore,
identity authentication scheme is used to register the nodes
and then authenticate them. The unknown nodes first register
themselves and then authenticate them to enter in the network.
In this way, only legitimate nodes become a part of the
network. The LEACH protocol is integrated with blockchain to
enhance the network lifetime because CHs with low energy are
replaced by highest energy CH node. On other side, identity
authentication scheme is used to make the network more
secure because only legitimate nodes can enter in the network.
In the future work, services will be provided to legitimate
nodes. The sensed data will be stored in a storage system.
Also, the computational cost will be checked as comparison
for authentication and storage.
REFERENCES
[1] Fu, M. H. (2020). Integrated Technologies of Blockchain and Biometrics
Based on Wireless Sensor Network for Library Management. Information
Technology and Libraries, 39(3).
[2] Kumari, S., and Om, H. (2016). Authentication protocol for wireless sen-
sor networks applications like safety monitoring in coal mines. Computer
Networks, 104, 137-154.
[3] Jiang, Q., Zeadally, S., Ma, J., and He, D. (2017). Lightweight three-
factor authentication and key agreement protocol for internet-integrated
wireless sensor networks. IEEE Access, 5, 3376-3392.
[4] Farooq, H., Arshad, M. U., Akhtar, M. F., Abbas, S., Zahid, B., Javaid,
N. (2019, November). Block-VN: A distributed blockchain-based effi-
cient communication and storage system. In International Conference on
Broadband and Wireless Computing, Communication and Applications
(pp. 56-66). Springer, Cham.
[5] Padmavathi, U., and Rajagopalan, N. (2021). Concept of Blockchain
Technology and Its Emergence. In Blockchain Applications in IoT
Security (pp. 1-20). IGI Global.
[6] Moinet, A., Darties, B., and Baril, J. L. (2017). Blockchain based trust
and authentication for decentralized sensor networks. arXiv preprint
arXiv:1706.01730.
[7] Abubaker, Z., Gurmani, M. U., Sultana, T., Rizwan, S., Azeem, M.,
Iftikhar, M. Z., Javaid, N. (2019, November). Decentralized Mecha-
nism for Hiring the Smart Autonomous Vehicles Using Blockchain.
In International Conference on Broadband and Wireless Computing,
Communication and Applications (pp. 733-746). Springer, Cham.
[8] Goyat, R., Kumar, G., Saha, R., Conti, M., Rai, M. K., Thomas, R., ... and
Hoon-Kim, T. (2020). Blockchain-based Data Storage with Privacy and
Authentication in Internet-of-Things. IEEE Internet of Things Journal.
[9] Abbas, S., Javaid, N. (2019, December). Blockchain based Vehicular Trust
Management and Less Dense Area Optimization. In 2019 International
Conference on Frontiers of Information Technology (FIT) (pp. 250-2505).
IEEE.
[10] Christidis, K., and Devetsikiotis, M. (2018). Blockchains and smart
contracts for the Internet of Things. Journal of Fintech, Blockchain, and
Smart Contracts, 1(1), 7-12.
[11] Magazzeni, D., McBurney, P., and Nash, W. (2017). Validation and
verification of smart contracts: A research agenda. Computer, 50(9), 50-
57.
[12] Haseeb, K., Islam, N., Almogren, A., and Din, I. U. (2019). Intrusion
prevention framework for secure routing in WSN-based mobile Internet
of Things. Ieee Access, 7, 185496-185505.
[13] Hong, S. (2020). P2P networking based internet of things (IoT) sensor
node authentication by Blockchain. Peer-to-Peer Networking and Appli-
cations, 13(2), 579-589.
[14] Cui, Z., Fei, X. U. E., Zhang, S., Cai, X., Cao, Y., Zhang, W., and Chen,
J. (2020). A hybrid BlockChain- based identity authentication scheme for
multi-WSN. IEEE Transactions on Services Computing, 13(2), 241-251.
[15] Kolumban-Antal, G., Lasak, V., Bogdan, R., and Groza, B. (2020). A
Secure and Portable Multi-Sensor Module for Distributed Air Pollution
Monitoring. Sensors, 20(2), 403.
[16] Ramezan, G., and Leung, C. (2018). A blockchain-based contractual
routing protocol for the internet of things using smart contracts. Wireless
Communications and Mobile Computing, 2018.
[17] Xu, J., Meng, X., Liang, W., Zhou, H., and Li, K. C. (2020). A secure
mutual authentication scheme of blockchain-based in WBANs. China
Communications, 17(9), 34-49.
[18] Ren, Y., Liu, Y., Ji, S., Sangaiah, A. K., and Wang, J. (2018). Incentive
mechanism of data storage based on blockchain for wireless sensor
networks. Mobile Information Systems, 2018.
[19] Uddin, M. A., Stranieri, A., Gondal, I., and Balasurbramanian, V.
(2019). A lightweight blockchain based framework for underwater iot.
Electronics, 8(12), 1552.
[20] Liu, M., Yu, F. R., Teng, Y., Leung, V. C., and Song, M. (2018).
Computation offloading and content caching in wireless blockchain
networks with mobile edge computing. IEEE Transactions on Vehicular
Technology, 67(11), 11008-11021.
[21] Liu, Y., Wang, K., Lin, Y., and Xu, W. (2019). LightChain: A
Lightweight Blockchain System for Industrial Internet of Things. IEEE
Transactions on Industrial Informatics, 15(6), 3571-3581.
[22] Feng, H., Wang, W., Chen, B., and Zhang, X. (2020). Evaluation on
frozen shellfish quality by blockchain based multi-sensors monitoring and
SVM algorithm during cold storage. IEEE Access, 8, 54361-54370.
[23] Danzi, P., Kalør, A. E., Stefanovi´
c, ˇ
C., and Popovski, P. (2019). Delay
and communication tradeoffs for blockchain systems with lightweight IoT
clients. IEEE Internet of Things Journal, 6(2), 2354-2365.
[24] Rathee, G., Balasaraswathi, M., Chandran, K. P., Gupta, S. D., and
Boopathi, C. S. (2020). A secure IoT sensors communication in industry
4.0 using blockchain technology. Journal of Ambient Intelligence and
Humanized Computing, 1-13.
[25] Jia, B., Zhou, T., Li, W., Liu, Z., and Zhang, J. (2018). A blockchain-
based location privacy protection incentive mechanism in crowd sensing
networks. Sensors, 18(11), 3894.
[26] Tian, Y., Wang, Z., Xiong, J., and Ma, J. (2020). A blockchain-based
secure key management scheme with trustworthiness in DWSNs. IEEE
Transactions on Industrial Informatics, 16(9), 6193-6202.
[27] Mori, S. (2018). Secure caching scheme by using blockchain for
information-centric network-based wireless sensor networks. Journal of
Signal Processing, 22(3), 97-108.
[28] Sharma, P. K., and Park, J. H. (2018). Blockchain based hybrid network
architecture for the smart city. Future Generation Computer Systems, 86,
650-655.
[29] Guerrero-Sanchez, A. E., Rivas-Araiza, E. A., Gonzalez-Cordoba, J. L.,
Toledano-Ayala, M., and Takacs, A. (2020). Blockchain mechanism and
symmetric encryption in a wireless sensor network. Sensors, 20(10), 2798.
[30] Rovira-Sugranes, A., and Razi, A. (2019). Optimizing the Age of
Information for Blockchain Technology With Applications to IoT Sensors.
IEEE Communications Letters, 24(1), 183-187.
[31] Sergii, K., and Prieto-Castrillo, F. (2018). A rolling blockchain for a
dynamic WSNs in a smart city. arXiv preprint arXiv:1806.11399.
[32] Shahbazi, Z., and Byun, Y. C. (2020). Towards a secure thermal-
energy aware routing protocol in Wireless Body Area Network based
on blockchain technology. Sensors, 20(12), 3604.
[33] Kim, T. H., Goyat, R., Rai, M. K., Kumar, G., Buchanan, W. J., Saha,
R., and Thomas, R. (2019). A novel trust evaluation process for secure
localization using a decentralized blockchain in wireless sensor networks.
IEEE Access, 7, 184133-184144.
[34] She, W., Liu, Q., Tian, Z., Chen, J. S., Wang, B., and Liu, W. (2019).
Blockchain trust model for malicious node detection in wireless sensor
networks. IEEE Access, 7, 38947-38956.
[35] Xu, Y., Ren, J., Wang, G., Zhang, C., Yang, J., and Zhang, Y. (2019).
A blockchain-based nonrepudiation network computing service scheme
for industrial IoT. IEEE Transactions on Industrial Informatics, 15(6),
3632-3641.
[36] Kumar, M. H., Mohanraj, V., Suresh, Y., Senthilkumar, J., and Nagalalli,
G. (2020). Trust aware localized routing and class based dynamic block
chain encryption scheme for improved security in WSN. Journal of
Ambient Intelligence and Humanized Computing, 1-9.
[37] Goyat, R., Kumar, G., Rai, M. K., Saha, R., Thomas, R., and Kim, T. H.
(2020). Blockchain Powered Secure Range-Free Localization in Wireless
Sensor Networks. Arabian Journal for Science and Engineering, 45(8),
6139-6155.
[38] Rahman, A., Islam, M. J., Khan, M. S. I., Kabir, S., Pritom, A. I., and
Karim, M. R. (2020). Block-SDoTCloud: Enhacing Security of Cloud
Storage through Blockchain-based SDN in IoT Network.
[39] Rathore, S., Kwon, B. W., and Park, J. H. (2019). BlockSecIoTNet:
Blockchain-based decentralized security architecture for IoT network.
Journal of Network and Computer Applications, 143, 167-177.
[40] Lee, Y., Rathore, S., Park, J. H., and Park, J. H. (2020). A blockchain-
based smart home gateway architecture for preventing data forgery.
Human-centric Computing and Information Sciences, 10(1), 1-14.
[41] Heinzelman, W. R., Chandrakasan, A., Balakrishnan, H. (2000, January).
Energy-efficient communication protocol for wireless microsensor net-
works. In Proceedings of the 33rd annual Hawaii international conference
on system sciences (pp. 10-pp). IEEE.
Article
This paper proposes a blockchain based nodes' authentication model for the internet of sensor things (IoST). The nodes in the network are authenticated based on their credentials to make the network free from malicious nodes. In IoST, sensor nodes gather the information from the environment and send it to the cluster heads (CHs) for additional processing. CHs aggregate the sensed information. Therefore, their energy rapidly depletes due to extra workload. To solve this issue, we proposed distance, degree, and residual energy based low-energy adaptive clustering hierarchy (DDR-LEACH) protocol. DDR-LEACH is used to replace CHs with the ordinary nodes based on maximum residual energy, degree and minimum distance from BS. Furthermore, storing a huge amount of data in the blockchain is very costly. To tackle this issue, an external data storage, named as interplanetary file system (IPFS), is used. Furthermore, for ensuring data security in IPFS, AES 128-bit is used, which performs better than the existing encryption schemes. Moreover, a huge computational cost is required using a proof of work consensus mechanism to validate transactions. To solve this issue, proof of authority (PoA) consensus mechanism is used in the proposed model. The simulation results are carried out, which show the efficiency and effectiveness of the proposed system model. The DDR-LEACH is compared with LEACH and the simulation results show that DDR-LEACH outperforms LEACH in terms of energy consumption, throughput and improvement in network lifetime with CH selection mechanism. Moreover, transaction cost is computed, which is reduced by PoA during data storage on IPFS and service provisioning. Furthermore, the time is calculated in the comparison of AES 128-bit scheme with existing scheme. The formal security analysis is performed to check the effectiveness of smart contract against attacks. Also, two different attacks, MITM and Sybil, are induced in our system to show our system model's resilience against cyber attacks.
Chapter
Full-text available
Blockchain refers to a distributed ledger technology that helps people to regulate and manage their information without any intermediaries. This technology emerges as a promising panacea for authentication and authorization with potential for use in every possible domain including financial, manufacturing, educational institutions, etc. Blockchain has its birth through the concept of Bitcoin, a digital cryptocurrency by Satoshi Nakamoto, called as Blockchain 1.0. Blockchain 2.0 came into existence in 2014 with Ethereum and smart contracts. The challenges such as scalability, interoperability, sustainability, and governance led to the next generation of Blockchain also called as IOTA, a blockchainless cryptocurrency for the internet of things runs on the top of their own ledger called Tangle, which is immune towards quantum computers. This disruptive technology evolved to provide cross chain support and more security through Blockchain 4.0. Finally, the chapter concludes by discussing the various applications of this technology and its advantages and security issues.
Article
Full-text available
The emergence of biomedical sensor devices, wireless communication, and innovation in other technologies for healthcare applications result in the evolution of a new area of research that is termed as Wireless Body Area Networks (WBANs). WBAN originates from Wireless Sensor Networks (WSNs), which are used for implementing many healthcare systems integrated with networks and wireless devices to ensure remote healthcare monitoring. WBAN is a network of wearable devices implanted in or on the human body. The main aim of WBAN is to collect the human vital signs/physiological data (like ECG, body temperature, EMG, glucose level, etc.) round-the-clock from patients that demand secure, optimal and efficient routing techniques. The efficient, secure, and reliable designing of routing protocol is a difficult task in WBAN due to its diverse characteristic and restraints, such as energy consumption and temperature-rise of implanted sensors. The two significant constraints, overheating of nodes and energy efficiency must be taken into account while designing a reliable blockchain-enabled WBAN routing protocol. The purpose of this study is to achieve stability and efficiency in the routing of WBAN through managing temperature and energy limitations. Moreover, the blockchain provides security, transparency, and lightweight solution for the interoperability of physiological data with other medical personnel in the healthcare ecosystem. In this research work, the blockchain-based Adaptive Thermal-/Energy-Aware Routing (ATEAR) protocol for WBAN is proposed. Temperature rise, energy consumption, and throughput are the evaluation metrics considered to analyze the performance of ATEAR for data transmission. In contrast, transaction throughput, latency, and resource utilization are used to investigate the outcome of the blockchain system. Hyperledger Caliper, a benchmarking tool, is used to evaluate the performance of the blockchain system in terms of CPU utilization, memory, and memory utilization. The results show that by preserving residual energy and avoiding overheated nodes as forwarders, high throughput is achieved with the ultimate increase of the network lifetime. Castalia, a simulation tool, is used to evaluate the performance of the proposed protocol, and its comparison is made with Multipath Ring Routing Protocol (MRRP), thermal-aware routing algorithm (TARA), and Shortest-Hop (SHR). Evaluation results illustrate that the proposed protocol performs significantly better in balancing of temperature (to avoid damaging heat effect on the body tissues) and energy consumption (to prevent the replacement of battery and to increase the embedded sensor node life) with efficient data transmission achieving a high throughput value.
Article
Full-text available
The Internet of Things (IoT) paradigm allows the connection and exchange of information between millions of smart devices. This paradigm grows and develops exponentially as do the risks and attacks on IoT infrastructures. Security, privacy, reliability, and autonomy are the most important requirements in IoT Systems. If these issues are not guaranteed, the IoT system could be susceptible to malicious users and malicious use. In centralized IoT systems, attacks and risks are greater, especially when data is transmitted between devices and shared with other organizations. To avoid these types of situations, this work presents a decentralized system that guarantees the autonomy and security of an IoT system. The proposed methodology helps to protect data integrity and availability based on the security advantages provided by blockchain and the use of cryptographic tools. The accuracy of the proposed methodology was measured on a temperature and humidity sensing IoT-based Wireless Sensor Network (WSN). The obtained results prove that the proposal fulfils the main requirements of an IoT system. It is autonomous, secure to share and send information between devices and users, has privacy, it is reliable, and the information is available in the infrastructure. Furthermore, this research demonstrates that the proposal is less susceptible to the most frequent attacks against IoT systems, such as linking attack, man in the middle, and Distributed Denial of Service (DDoS) attack.
Article
Full-text available
The modern wireless sensor network has great impact in the development of various domains of applications. The presence of malicious nodes introduces various threats and challenges to the network services. Different algorithms have been proposed towards the data security but not achieved the expected performance. Towards performance hike, a novel trust aware localized routing and class based dynamic encryption scheme has been presented. The method first discovers the route to reach the destination and transmit the data packet. But the localized nature of each hop in the route estimates the trust measure for each neighbor according to their prior involvement in data transmission and number of retransmission of the same packets with other neighbor, number of successful transmission. By identifying the values of those parameters, the value of trusted data forwarding support (TDFS) is measured. According to the TDFS value of several routes, a route with the specific neighbor only selected for route selection. On the other side, the method maintains and classifies the data being transmitting into number of classes. Further, the method uses different signature and encryption schemes for various classes. The data has been encrypted with class specific scheme and key before transmission. The method generates a block chain where each block contains the part of encrypted data and represented by a hash and pointer to the next block. The same has been reversed to produce original data from the encrypted key. The method introduces higher performance data security and improves the overall network performance.
Article
Full-text available
Industrial IoT in the advancement of organizations consigns to the next level in order to trace and manage every single activity of their entities. However, the interdependence, implementation and communication among such wireless devices also known as IoT devices that lead to various secrecy and personnel concerns. Even though the use of smart sensors in industries assists and reduces human efforts with the increased quality besides of enhanced production cost. Several attacks may further encountered by various attackers by hacking several sensors/objects/devices activities. In this paper, in order to preserve transparency and secure each and every activity of smart sensors, we have proposed a secure wireless mechanism using Blockchain technology that stores extorted proceedings of each record into number of blocks. Further, the simulation results of proposed blockchain mechanism are executed against various security transmission processes. In addition, the simulated results are scrutinized besides traditional mechanism and verified over certain metrics such as Probability of attack success, ease of attack detection by the system, falsification attack, authentication delay and probabilistic scenarios to appraise the authenticity of IoT devices.
Chapter
In the Internet of Things (IoT), sensor networks form the basis for interactions with the environment and are seeing accelerated development. This chapter introduces the IoT challenges that we are going to examine here. These are challenges that are related to functioning, confidentiality and security. The chapter describes the concepts of authentication and integrity as well as the concepts of reputation and trust. It introduces the authors' contribution, the Blockchain Authentication and Trust Module (BATM) architecture. The chapter presents the notations used the general architecture of the BATM, and describes how BATM aims to respond to authentication needs by specifying the mechanisms that we have implemented. It explores the evaluation of BATM architecture through simulations. The chapter concludes the relevance of BATM with respect to the results obtained and also explains the possible future prospects of this work.
Conference Paper
Software Defined Networking (SDN) and Blockchain (BC) are the most recent research trends in emerging technology. These technologies have currently been used in the IoT networking environment for various purposes, such as protection, stability, scalability, confidentiality, and so on. Such techniques can be used in this regard to effectively provide security, privacy, and confidentiality to cloud storage. In this paper, the authors proposed Block-SDoTCloud architecture to significantly enhance security within the cloud storage network. In order to give the cloud storage environment the requisite facilities, two leading technologies, i.e., SDN and Blockchain were applied. The centralized SDN controller provided the proposed model with tremendous reliability, versatility, and load balancing in one side while on the other hand, a distributed Blockchain created a deep trust between the transaction levels resulting into effective protection for the presented scheme. The efficiency of the proposed architecture is justified through close observation of simulation with a careful selection of relevant parameters.
Article
Wireless Body Area Networks (WBANs) refer to small sensor network that consists of sensor devices mounted on the surface of the body or implanted in the body, as such networks are employed to harvest physiological data of the human body or to act as an assistant regulator of several specific physiological indicators of the human body. The sensor devices transmit the harvested human physiological data to the local node via a public channel. Before transmitting data, the sensor device and the local node should perform mutual authentication and key agreement. It is proposed in this paper a secure mutual authentication scheme of blockchain-based in WBANs. To analyze the security of this scheme, formal security analysis, and informal security analysis are used, then the computation and communication costs are compared with those of the relevant schemes. Relevant experimental results reveal that the proposed scheme exhibit more effective control over energy consumption and promising.
Article
The Internet of Things (IoT) is built on a strong internet infrastructure and many wireless sensor devices. Presently, Radio Frequency Identification embedded (RFID-embedded) smart cards are ubiquitous, used for many things including student ID cards, transportation cards, bank cards, prepaid cards, and citizenship cards. One example of places that require smart cards is libraries. Each library, such as a university library, city library, local library, or community library, has its own card and the user must bring the appropriate card to enter a library and borrow material. However, it is inconvenient to bring various cards to access different libraries. Wireless infrastructure has been well developed and IoT devices are connected through this infrastructure. Moreover, the development of biometric identification technologies has continued to advance. Blockchain methodologies have been successfully adopted in various fields. This paper proposes the BlockMetrics library based on integrated technologies using blockchain and finger-vein biometrics, which are adopted into a library collection management and access control system. The library collection is managed by image recognition, RFID, and wireless sensor technologies. In addition, a biometric system is connected to a library collection control system, enabling the borrowing procedure to consist of only two steps. First, the user adopts a biometric recognition device for user authentication and then performs a collection scan with the RFID devices. All the records are recorded in a personal borrowing blockchain, which is a peer-to-peer transfer system and permanent data storage. In addition, the user can check the status of his collection across various libraries in his personal borrowing blockchain. The BlockMetrics library is based on an integration of technologies that include blockchain, biometrics, and wireless sensor technologies to improve the smart library.
Article
Internet of Things (IoTs) composed of large number of sensing devices with a variety of features applicable for various applications. In such scenarios, due to low data handling capabilities, limited storage and security aspects, it is quite challenging to protect networks against illegal information access and utilizes storage efficiently. Though researchers provide various solutions for security and data storage, but a few solutions are appropriate for WSNs enabled IoTs. Therefore, a blockchain-based decentralized framework integrated with authentication and privacy preserving schemes is developed for the secure communication in wireless sensor networks (WSNs) enabled IoTs. Registration, certification and revocation process are employed for the communication with sensor nodes and Base Station (BS) in a cloud computing environment. In this scheme cluster heads forward the collected information to the BS. Consequently, BS records all the key parameters on the distributed blockchain and large data is forwarded to clouds for the storage. The revoked certificates of all malicious nodes are eliminated from blockchain by BS. The performance of the proposed scheme is scrutinized in terms of detection accuracy, certification delay, computational, and communicational overheads. The simulated results, comparative analysis and security validation supports the superiority of the proposed solution over the existing approaches.