Reputation-based secure spectrum situation fusion in 
distributed cognitive radio networks

doi:10.1016/S1005-8885(15)60659-8

中国邮电高校学报(英文) ›› 2015, Vol. 22 ›› Issue (3): 110-117.doi: 10.1016/S1005-8885(15)60659-8

Reputation-based secure spectrum situation fusion in distributed cognitive radio networks

李方伟¹,Li Fangwei, Liu Fan, Zhu Jiang, Nie Yifang

School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications

收稿日期:2014-10-02 修回日期:2015-03-19 出版日期:2015-06-30 发布日期:2015-06-24
通讯作者: Liu Fan, E-mail: 1021013631@qq.com E-mail:1021013631@qq.com
基金资助:
the Key Project of National Nature Science Foundations of China (61271260).

Reputation-based secure spectrum situation fusion in distributed cognitive radio networks

Li Fangwei, Liu Fan, Zhu Jiang, Nie Yifang

School of Communication and Information Engineering, Chongqing University of Posts and Telecommunications

Received:2014-10-02 Revised:2015-03-19 Online:2015-06-30 Published:2015-06-24
Contact: Liu Fan, E-mail: 1021013631@qq.com E-mail:1021013631@qq.com
Supported by:
the Key Project of National Nature Science Foundations of China (61271260).

摘要/Abstract

摘要： In distributed cognitive radio (CR) network, the cooperative spectrum situation sensing based on consensus scheme may be disrupted by spectrum sensing data falsification (SSDF) attacks. In this paper, a secure spectrum situation fusion scheme based on reputation is proposed to counter attacks. The neighboring nodes of secondary users (SUs) get the corresponding dynamic trust value according to their behavior, which restrict the impact of the malicious behavior on the premise to ensure information interaction of normal nodes. Theoretical analysis and simulation results show that the consensus fusion scheme based on reputation has better performance than the existing algorithm which eliminates the neighboring node with the biggest deviation value from mean value. It demonstrates that the proposed scheme not only achieves better convergence properties but also has higher detection probability than the existing scheme in the process of spectrum situation fusion.

关键词: cognitive radio; spectrum situation fusion; secure; consensus; spectrum sensing data falsification (SSDF) attack

Abstract: In distributed cognitive radio (CR) network, the cooperative spectrum situation sensing based on consensus scheme may be disrupted by spectrum sensing data falsification (SSDF) attacks. In this paper, a secure spectrum situation fusion scheme based on reputation is proposed to counter attacks. The neighboring nodes of secondary users (SUs) get the corresponding dynamic trust value according to their behavior, which restrict the impact of the malicious behavior on the premise to ensure information interaction of normal nodes. Theoretical analysis and simulation results show that the consensus fusion scheme based on reputation has better performance than the existing algorithm which eliminates the neighboring node with the biggest deviation value from mean value. It demonstrates that the proposed scheme not only achieves better convergence properties but also has higher detection probability than the existing scheme in the process of spectrum situation fusion.

Key words: cognitive radio; spectrum situation fusion; secure; consensus; spectrum sensing data falsification (SSDF) attack

中图分类号:

TN915.08

Li Fangwei, Liu Fan, Zhu Jiang, Nie Yifang. Reputation-based secure spectrum situation fusion in distributed cognitive radio networks [J]. Acta Metallurgica Sinica(English letters), 2015, 22(3): 110-117.

参考文献

1. Li Z Q, Yu F R, Huang M Y. A distributed consensus-based cooperative spectrum-sensing scheme in cognitive radios. IEEE Transactions on Vehicular Technology, 2010, 59(1): 383?393 2. Zhang W L, Wang Z, Guo Y, et al. Distributed cooperative spectrum sensing based on weighted average consensus. Proceedings of the IEEE Global Communications Conference (GLOBECOM’11), Dec 5?9, 2011, Houston, TX, USA. Piscataway, NJ, USA: IEEE, 2011: 6p 3. Wang M C, Liu B, Zhang C. Detection of collaborative SSDF attacks using abnormality detection algorithm in cognitive radio networks. Proceedings of the IEEE International Conference on Communications (ICC’13), Jun 9?13, 2013, Budapest, Hungary. Piscataway, NJ, USA: IEEE, 2013: 342?346 4. Chen C L, Song M, Xin C S. A density based scheme to countermeasure spectrum sensing data falsification attacks in cognitive radio networks. Proceedings of the IEEE Global Communications Conference (GLOBECOM’13), Dec 9?13, 2013, Atlanta, GA, USA. Piscataway, NJ, USA: IEEE, 2013: 623?628 5. Rawat A S, Anand P, Chen H, et al. Collaborative spectrum sensing in the presence of Byzantine attacks in cognitive radio networks. IEEE Transactions on Signal Processing, 2011, 59(2): 774?786 6. Kaligineedi P, Khabbazian M, Bhargava V K. Malicious user detection in a cognitive radio cooperative sensing system. IEEE Transactions on Wireless Communications, 2010, 9(8): 2488?2497 7. Tang H, Yu F R, Huang M, et al. Distributed consensus-based security mechanisms in cognitive radio mobile ad hoc networks. IET Communications, 2012, 6(8): 974?983 8. Yu F R, Huang M Y, Tang H. Biologically inspired consensus-based spectrum sensing in mobile ad hoc networks with cognitive radios. IEEE Network, 2010, 24(3): 26?30 9. Yan Q B, Li M, Jiang T, et al. Vulnerability and protection for distributed consensus-based spectrum sensing in cognitive radio networks. Proceedings of the 31st Annual Joint Conference of the IEEE Computer and Communications (INFOCOM’12), Mar 25?30, 2012, Orlando, FL, USA. Piscataway, NJ, USA: IEEE, 2012: 900?908 10. Liu S, Zhu H J, Li S, et al. An adaptive deviation-tolerant secure scheme for distributed cooperative spectrum sensing. Proceedings of the IEEE Global Communications Conference (GLOBECOM’12), Dec 3?7, 2012, Anaheim, CA, USA. Piscataway, NJ, USA: IEEE, 2012: 603?608 11. Feng J Y, Zhang Y Q, Lu G Y, et al. Defend against collusive SSDF attack using trust in cooperative spectrum sensing environment. Proceedings of the 12th IEEE International Conference on Trust, Security and Privacy in Computing and Communications (TrustCom’13), Jul 16?18, 2013, Melbourne, Australia. Piscataway, NJ, USA: IEEE, 2013: 1656?1661 12. Liang Y C, Zeng Y H, Peh E C Y, et al. Sensing-throughput tradeoff for cognitive radio networks. IEEE Transactions on Wireless Communications, 2008, 7(4): 1326?1337 13. Zhou M, Shen J F, Chen H F, et al. A cooperative spectrum sensing scheme based on the Bayesian reputation model in cognitive radio networks. Proceedings of the 2013 IEEE Wireless Communications and Networking Conference (WCNC'13), Apr 7?10, 2013, Shanghai, China. Piscataway, NJ, USA: IEEE, 2013: 614?619 14. Das A, Islam M M. Securedtrust: A dynamic trust computation model for secured communication in multiagent systems. IEEE Transactions on Dependable and Secure Computing, 2012, 9(2): 261?274 15. Chang J S, Wang H M, Ying G. DyTrust: A time-frame based dynamic trust model for P2P systems. Chinese Journal of Computers, 2006, 29(8): 1301?1307 (in: Chinese)

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Reputation-based secure spectrum situation fusion in distributed cognitive radio networks

Reputation-based secure spectrum situation fusion in distributed cognitive radio networks

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