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http://dx.doi.org/10.3837/tiis.2021.11.019

Throughput and Interference for Cooperative Spectrum Sensing: A Malicious Perspective  

Gan, Jipeng (School of Communication Engineering, Hangzhou Dianzi University)
Wu, Jun (School of Communication Engineering, Hangzhou Dianzi University)
Zhang, Jia (School of Communication Engineering, Hangzhou Dianzi University)
Chen, Zehao (School of Communication Engineering, Hangzhou Dianzi University)
Chen, Ze (School of Communication Engineering, Hangzhou Dianzi University)
Publication Information
KSII Transactions on Internet and Information Systems (TIIS) / v.15, no.11, 2021 , pp. 4224-4243 More about this Journal
Abstract
Cognitive radio (CR) is a feasible intelligent technology and can be used as an effective solution to spectrum scarcity and underutilization. As the key function of CR, cooperative spectrum sensing (CSS) is able to effectively prevent the harmful interference with primary users (PUs) and identify the available spectrum resources by exploiting the spatial diversity of multiple secondary users (SUs). However, the open nature of the cognitive radio networks (CRNs) framework makes CSS face many security threats, such as, the malicious user (MU) launches Byzantine attack to undermine CRNs. For this aim, we make an in-depth analysis of the motive and purpose from the MU's perspective in the interweave CR system, aiming to provide the future guideline for defense strategies. First, we formulate a dynamic Byzantine attack model by analyzing Byzantine behaviors in the process of CSS. On the basis of this, we further make an investigation on the condition of making the fusion center (FC) blind when the fusion rule is unknown for the MU. Moreover, the throughput and interference to the primary network are taken into consideration to evaluate the impact of Byzantine attack on the interweave CR system, and then analyze the optimal strategy of Byzantine attack when the fusion rule is known. Finally, theoretical proofs and simulation results verify the correctness and effectiveness of analyses about the impact of Byzantine attack strategy on the throughput and interference.
Keywords
Cooperative spectrum sensing; Byzantine attack; Malicious perspective; Throughput and interference;
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1 Y. Al-Mathehaji, S. Boussakta, M. Johnston and H. Fakhrey, "Defeating SSDF attacks with trusted nodes assistance in cognitive radio networks," IEEE Sensors Letters, vol. 1, no. 4, pp. 1-4, Aug. 2017.
2 Z. Sun, Z. Xu, Z. Chen, X. Ning and L. Guo, "Reputation-based spectrum sensing strategy selection in cognitive radio Ad Hoc networks," Sensors, vol. 18, no. 12, pp. 4377, Dec. 2018.   DOI
3 B. Kailkhura, Y. S. Han, S. Brahma and P. K. Varshney, "Distributed Bayesian detection in the presence of Byzantine data," IEEE Transactions on Signal Processing, vol. 63, no. 19, pp. 5250- 5263, Oct. 2015.   DOI
4 A. A. Sharifi and M. J. Musevi Niya, "Defense against SSDF attack in cognitive radio networks: Attack-aware collaborative spectrum sensing approach," IEEE Communications Letters, vol. 20, no. 1, pp. 93-96, Jan. 2016.   DOI
5 S. Nallagonda, Y. R. Kumar and P. Shilpa, "Analysis of hard-decision and soft-data fusion schemes for cooperative spectrum sensing in Rayleigh fading channel," in Proc of 2017 IEEE 7th International Advance Computing Conference, Hyderabad, India, pp. 220-225, 2017.
6 J. Wu, Y. Yu, T. Song and J. Hu, "Robust reputation management mechanism in cooperative spectrum sensing," Electronics Letters, vol. 55, no. 21, pp. 1128-1130, Oct. 2019.   DOI
7 H. O. Shazly, A. Saafan, H. E. Badawy and H. M. E. Hennawy, "Performance of analysis cognitive radio with cooperative sensing under malicious attacks over Nakagami faded channels," Wireless Engineering and Technology, vol. 7, no. 2, pp. 67-74, Apr. 2016.   DOI
8 J. Ren, Y. Zhang, Q. Ye, K. Yang, K. Zhang and X. S. Shen, "Exploiting secure and energyefficient collaborative spectrum sensing for cognitive radio sensor networks," IEEE Transactions on Wireless Communications, vol. 15, no. 10, pp. 6813-6827, Oct. 2016.   DOI
9 J. Parras and S. Zazo, "Learning attack mechanisms in wireless sensor networks using Markov decision processes," Expert Systems with Applications, vol. 122, pp. 376-387, May 2019.   DOI
10 J. Wu, Y. Yu, T. Song and J. Hu, "Sequential 0/1 for cooperative spectrum sensing in the presence of strategic Byzantine attack," IEEE Wireless Communications Letters, vol. 8, no. 2, pp. 500-503, Apr. 2019.   DOI
11 A. A. Sharifi and M. Mofarreh-Bonab, "Spectrum sensing data falsification attack in cognitive radio networks: An analytical model for evaluation and mitigation of performance degradation," AUT Journal of Electrical Engineering, vol. 50, no. 1, pp. 43-50, 2018.
12 J. Wu, T. Song, Y. Yu, C. Wang and J. Hu, "Generalized Byzantine attack and defense in cooperative spectrum sensing for cognitive radio networks," IEEE Access, vol. 6, pp. 53272-53286, Aug. 2018.   DOI
13 F. Ye, X. Zhang, Y. Li and C. Tang, "Faithworthy collaborative spectrum sensing based on credibility and evidence theory for cognitive radio networks," Symmetry, vol. 9, no. 3, pp. 36, Mar. 2017.   DOI
14 J. Wu, T. Song, Y. Yue, C. Wang and J. Hu, "Sequential cooperative spectrum sensing in the presence of dynamic Byzantine attack for mobile networks," PloS one, vol. 13, no. 7, Jul. 2018.
15 W. Hashlamoun, S. Brahma and P. K. Varshney, "Mitigation of Byzantine attacks on distributed detection systems using audit bits," IEEE Transactions on Signal and Information Processing over Networks, vol. 4, no. 1, pp. 18-32, Mar. 2018.   DOI
16 L. Zhang, G. Ding, Q. Wu, Y. Zou, Z. Han and J. Wang, "Byzantine attack and defense in cognitive radio networks: A survey," IEEE Communications Surveys and Tutorials, vol. 17, no. 3, pp. 1342-1363, Apr. 2015.   DOI
17 P. Verma and B. Singh, "On the decision fusion for cooperative spectrum sensing in cognitive radio networks," Wireless Networks, vol. 23, pp. 2253-2262, May. 2016.   DOI
18 J. Wu, Y. Yu, H. Zhu, T. Song and J. Hu, "Cost-benefit tradeoff of Byzantine attack in cooperative spectrum sensing," IEEE Systems Journal, vol. 14, no. 2, pp. 2532-2543, Jun. 2020.   DOI
19 Y. Liang, Y. Zeng, E. C. Y. Peh and A. T. Hoang, "Sensing-throughput tradeoff for cognitive radio networks," IEEE Transactions on Wireless Communications, vol. 7, no. 4, pp. 1326-1337, Apr. 2008.   DOI
20 J. Wu, Y. Chen, P. Li, J. Zhang, C. Wang, J. Tang et al., "Optimisation of virtual cooperative spectrum sensing for UAV-based interweave cognitive radio system," IET Communications, vol. 15, no. 10, pp. 1368-1379, Jan. 2021.   DOI
21 X. Luo, "Secure cooperative spectrum sensing strategy based on reputation mechanism for cognitive wireless sensor networks," IEEE Access, vol. 8, pp. 131361-131369, Jul. 2020.   DOI
22 N. Marchang, A. Taggu and A. K. Patra, "Detecting Byzantine attack in cognitive radio networks by exploiting frequency and ordering properties," IEEE Transactions on Cognitive Communications and Networking, vol. 4, no. 4, pp. 816-824, Dec. 2018.   DOI
23 P. Anand, A. S. Rawat, H. Chen and P. K. Varshney, "Collaborative spectrum sensing in the presence of Byzantine attacks in cognitive radio networks," in Proc of International Conference on COMmunication Systems and NETworks (COMSNETS), Bangalore, India, pp. 1-9, 2010.
24 A. S. Rawat, P. Anand, H. Chen and P. K. Varshney, "Collaborative spectrum sensing in the presence of Byzantine attacks in cognitive radio networks," IEEE Transactions on Signal Processing, vol. 59, no. 2, pp. 774-786, Feb. 2011.   DOI
25 Y. Gan, C. Jiang, N. C. Beaulieu, J. Wang and Y. Ren, "Secure collaborative spectrum sensing: A peer-prediction method," IEEE Transactions on Communications, vol. 64, no. 10, pp. 4283-4294, Oct. 2016.   DOI
26 T. Yucek and H. Arslan, "A survey of spectrum sensing algorithms for cognitive radio applications," IEEE Communications Surveys and Tutorials, vol. 11, no. 1, pp. 116-130, Mar. 2009.   DOI
27 K. Zeng, P. Pawelczak and D. Cabric, "Reputation-based cooperative spectrum sensing with trusted nodes assistance," IEEE Communications Letters, vol. 14, no. 3, pp. 226-228, Mar. 2010.   DOI
28 X. L. Huang, Y. Xu, J. Wu and W. Zhang, "Non-cooperative spectrum sensing with historical sensing data mining in cognitive radio," IEEE Transactions on Vehicular Technology, vol. 66, no. 10, pp. 8863-8871, Oct. 2017.   DOI
29 W. Wang, L. Chen, K. G. Shin and L. Duan, "Thwarting intelligent malicious behaviors in cooperative spectrum sensing," IEEE Transactions on Mobile Computing, vol. 14, no. 11, pp. 2392-2405, Nov. 2015.   DOI
30 L. Zhang, G. Nie, G. Ding, Q. Wu, Z. Zhang and Z. Han, "Byzantine attacker identification in collaborative spectrum sensing: A robust defense framework," IEEE Transactions on Mobile Computing, vol. 18, no. 9, pp. 1992-2004, Sept. 2019.   DOI
31 G. I. Tsiropoulos, O. A. Dobre, M. H. Ahmed and K. E. Baddour, "Radio resource allocation techniques for efficient spectrum access in cognitive radio networks," IEEE Communications Surveys and Tutorials, vol. 18, no. 1, pp. 824-847, Oct. 2016.   DOI
32 S. Kar, S. Sethi and M. K. Bhuya, "Security challenges in cognitive radio network and defending against Byzantine attack: A survey," International Journal of Communication Networks and Distributed Systems, vol. 17, no. 2, pp. 120-146, Sep.2016.   DOI