Blockchain-Based Security Enhancement and Spectrum Sensing in Cognitive Radio Network

Khanna, Ashish; Rani, Poonam; Sheikh, Tariq; Gupta, Deepak; Kansal, Vineet; Rodrigues, Joel J. P. C.

doi:10.1007/s11277-021-08729-0

Cited by 34 publications

(18 citation statements)

References 27 publications

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“…There have been some works considering to use blockchain for DSS in the literature [14], [17]- [25]. Blockchain as a platform for spectrum allocation was proposed in [18], where secondary users (SUs) obtain the spectrum access right through buying the idle spectrum of primary users (PUs).…”

Section: Related Workmentioning

confidence: 99%

Multi-Operator Dynamic Spectrum Sharing for Wireless Communications: A Consortium Blockchain Enabled Framework

Wang

et al. 2023

IEEE Trans. Cogn. Commun. Netw.

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Section: Related Workmentioning

confidence: 99%

Multi-Operator Dynamic Spectrum Sharing for Wireless Communications: A Consortium Blockchain Enabled Framework

Wang

et al. 2023

IEEE Trans. Cogn. Commun. Netw.

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“…A set S ⊆ N is known as γ radius neighbor of n 0 . Get values of u 1 , u 2 , u 3 using ( 16), ( 17) and (18) 8:…”

Section: Density Aware Clusteringmentioning

confidence: 99%

“…Currently, information or data security is mainly focused on wired and wireless communication because of the large amount of data transmission, which suspects eavesdropping. Blockchain is used to improve data security by performing secure spectrum sensing and beamforming [17], [18]. Hence, more attention is given to physical layer security, which prevents the network from attackers such as eavesdropping, jamming and primary user emulation (PUE), spectrum sensing data falsification (SSDF), and attacks such as Byzantine, to handle spectrum scarcity for increasing QoS [19], [20].…”

Section: Introductionmentioning

confidence: 99%

BlockCRN-IoCV: Secure Spectrum Access and Beamforming for Defense Against Attacks in mmWave Massive MIMO CRN in 6G Internet of Connected Vehicles

Pari

Jaisankar

2022

IEEE Access

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Cognitive Radio (CR) is a wireless communication system that is used for intelligent vehicles to solve spectrum scarcity and improve the utilization of the spectrum. However, spectrum sensing and data sharing are difficult due to the presence of malicious nodes which degrades the performance. To overcome these issues, we proposed the BlockCRN-IoCV method which includes authentication, density aware clustering, dual agent based spectrum access and secure beamforming. Here, authentication is performed for both Primary Users (PUs) and Secondary Users (SUs) using the Hybrid Advanced Encryption Standard and Hyper-elliptic Curve Cryptography (AES-HCC) algorithm by considering ID, PUF and location which ensures the legitimacy of the users. To address the mobility of the vehicle we perform density aware clustering using Density aware Dynamic Radius Clustering (DADRC) by considering location, distance and direction for increasing throughput. After completing clustering, we perform efficient spectrum access by using the Dual Agent based Twin Delayed (DA-TD3) algorithm which includes two agents, the first agent performs spectrum sensing by considering SNR, noise level and trust, and the second agent performs spectrum allocation by considering Channel State Information (CSI), in which the CSI is predicted by Quasi-Newton Iterative Unscented Kalman Filter (QNIUKF) algorithm for effective data transmission. Finally, secure beamforming is performed using Bi-Gated Recurrent Neural Network (BiGRU-CapsNet) by considering CSI, beam score, array factor, and direction of angle. The simulation is carried out by OMNET++ and SUMO simulation tools and the performance of this work is evaluated by throughput, packet delivery ratio, SNR, detection accuracy, BER, and delay. The simulation result shows that the proposed work achieves superior performance compared to existing work for secure spectrum sensing and beamforming.

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“…Another, blockchain-based security and spectrum sensing method (BSSSM) was proposed for managing the spectrum and detecting malicious users in CRNs. 31 This BSSSM protocol adopted an adaptive threshold spectrum energy detection algorithm for spectrum sensing, such that the interference between PUs and SUs are completely prevented. Each individual block in this blockchain method represented PUs and finite amount of SUs in the network.…”

Section: F I G U R E 2 Integration Of Block Chain With Crn Toward Spe...mentioning

confidence: 99%

“…Khanna et al 31 Blockchain-based security and spectrum sensing method (BSSSM) It adopted adaptive threshold spectrum energy detection algorithm for spectrum sensing to prevent the interference between PUs and SUs…”

Section: Rajesh Babu and Amutha 30mentioning

confidence: 99%

Certificateless linkable ring signature‐based blockchains for securing cognitive radio networks

Kumari

Guru²,

Manoharan³

et al. 2022

Concurrency and Computation

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Rapid advancement in industrial applications of Internet of Things (IoT) has dramatically increased the number of Internet connected devices resulting in big challenges of scalability, adaptability, connectivity, and accessibility. Cognitive radio is efficient in handling spectrum allocation problem by facilitating the allocation of unlicensed spectrum dynamically to the IoT applications. However, cognitive radio network (CRN) capability of spectrum sensing is highly vulnerable to diversified number of security attacks. Malicious user disturbs the spectrum sensing potential and minimizes its accuracy by launching attacks during the detection of primary signal. In this article, certificateless linkable ring signature-based blockchains (CLRSB) is proposed for securing CRNs by achieving reliable discrimination between trustworthy users through cryptographic keys. It initially transformed the complete set of users such as PUs and SUs into the structure of blocks representing the smart contracts-based traditional public ledger blockchain that gets integrated to form a decentralized network for attaining improvement in efficient spectrum sensing. It adopted a mayfly optimization algorithm (MFOA)-improved CNN (MFOA-ICNN)-based spectrum sensing method for preventing the interference between PUs and SUs during spectrum access. It also used MFOA for optimizing the features with balanced trade-off between exploration and exploitation to identify the remarkable features that attributes toward efficient spectrum sensing. It specifically used CLRS for protecting information about the transaction initiator for the objective of protecting blockchain privacy. Simulation experiments of this CLRSB confirmed better response time and minimized frame loss on an average by 18.13% and 17.81%, better than the baseline schemes used for investigation.

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Blockchain-Based Security Enhancement and Spectrum Sensing in Cognitive Radio Network

Cited by 34 publications

References 27 publications

Multi-Operator Dynamic Spectrum Sharing for Wireless Communications: A Consortium Blockchain Enabled Framework

Multi-Operator Dynamic Spectrum Sharing for Wireless Communications: A Consortium Blockchain Enabled Framework

BlockCRN-IoCV: Secure Spectrum Access and Beamforming for Defense Against Attacks in mmWave Massive MIMO CRN in 6G Internet of Connected Vehicles

Certificateless linkable ring signature‐based blockchains for securing cognitive radio networks

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