基于复合熵和证据理论的抗SSDF攻击协作频谱感知方法

doi:10.12305/j.issn.1001-506X.2023.11.35

Abstract

Abstract:

Aiming at the problem of sensing performance deterioration caused by spectrum sensing data falsification (SSDF) attacks in cooperative spectrum sensing, when the proportion of malicious users in secondary users is less than half, an anti-SSDF attacks cooperative spectrum sensing method based on composite entropy and evidence theory is proposed. Firstly, secondary users compute basic probability assignment (BPA) information based on local perception statistics. Secondly, the fusion center calculates the distance value according to the BPA and performs entropy processing to obtain the composite entropy, and then uses the composite entropy as the weight to adjust the BPA information to reduce the weight of malicious users. Finally, in view of the disadvantages of Dempster's fusion formula in evidence theory, the weighted summation method is used to replace the traditional fusion formula. The simulation results show that, compared with the other existing methods, the proposed method has better sensing performance under different types of SSDF attacks.

Key words: cooperative spectrum sensing, spectrum sensing data falsification (SSDF), composite entropy, evidence theory

CLC Number:

TN92

Shenhao YUAN, Zengmao CHEN, Ming DIAO, Zhiguo SUN, Rongchen SUN. Cooperative spectrum sensing method against SSDF attacks based on composite entropy and evidence theory[J]. Systems Engineering and Electronics, 2023, 45(11): 3663-3670.

Figures/Tables 8

Fig.1

Fig.2

Table 1

Fig.3

Fig.4

Fig.5

Fig.6

Fig.7

References 23

1	LIANG Y C , CHEN K C , LI G Y , et al. Cognitive radio networking and communications: an overview[J]. IEEE trans.on Vehicular Technology, 2011, 60 (7): 3386- 3407. doi: 10.1109/TVT.2011.2158673
2	YUCEK T , ARSLAN H . A survey of spectrum sensing algorithms for cognitive radio applications[J]. IEEE Communications Surveys & Tutorials, 2009, 11 (1): 116- 130.
3	ALI A , HAMOUDA W . Advances on spectrum sensing for cognitive radio networks: theory and applications[J]. IEEE Communications Surveys & Tutorials, 2016, 19 (2): 1277- 1304.
4	GANESAN G , LI Y . Cooperative spectrum sensing in cognitive radio, part Ⅱ: multiuser networks[J]. IEEE Trans.on Wireless Communications, 2007, 6 (6): 2214- 2222. doi: 10.1109/TWC.2007.05776
5	AKYILDIZ I F , LO B F , BALAKRISHNAN R . Cooperative spectrum sensing in cognitive radio networks: a survey[J]. Physical Communication, 2011, 4 (1): 40- 62. doi: 10.1016/j.phycom.2010.12.003
6	PENG Q H, ZENG K, WANG J, et al. A distributed spectrum sensing scheme based on credibility and evidence theory in cognitive radio context[C]//Proc. of the IEEE 17th International Symposium on Personal, Indoor and Mobile Radio Communications, 2006.
7	NGUYEN-THANH N , KOO I . An enhanced cooperative spectrum sensing scheme based on evidence theory and reliability source evaluation in cognitive radio context[J]. IEEE Communications Letters, 2009, 13 (7): 492- 494. doi: 10.1109/LCOMM.2009.090043
8	周亚建, 刘凯, 肖林. 基于DS证据理论的加权协作频谱检测算法[J]. 通信学报, 2012, 33 (12): 19- 24.
	ZHOU Y X , LIU K , XIAO L . Weighted cooperative spectrum sensing algorithm based on dempster-shafer evidence theory[J]. Journal of China Institute of Communications, 2012, 33 (12): 19- 24.
9	RAWAT A S , ANAND P , CHEN H , et al. Collaborative spectrum sensing in the presence of Byzantine attacks in cognitive radio networks[J]. IEEE Trans.on Signal Processing, 2010, 59 (2): 774- 786.
10	AL-MATHEHAJI Y , BOUSSAKTA S , JOHNSTON M , et al. Defeating SSDF attacks with trusted nodes assistance in cognitive radio networks[J]. IEEE Sensors Letters, 2017, 1 (4): 1- 4.
11	李文立, 郭凯红. DS证据理论合成规则及冲突问题[J]. 系统工程理论与实践, 2010, 30 (8): 1422- 1432.
	LI W L , GUO K H . Combination rules of DS evidence theory and conflict problem[J]. Systems Engineering-Theory & Practice, 2010, 30 (8): 1422- 1432.
12	HAN Y, CHEN Q, WANG J X. An enhanced DS theory cooperative spectrum sensing algorithm against SSDF attack[C]//Proc. of the IEEE 75th Vehicular Technology Conference, 2012.
13	于美婷, 赵林靖, 李钊. 基于DS证据理论的协作频谱感知改进方法[J]. 通信学报, 2014, 35 (3): 168- 173.
	YU M T , ZHAO L J , LI Z . Improved cooperative spectrum sensing scheme based on DS theory in cognitive radio network[J]. Journal on Communications, 2014, 35 (3): 168- 173.
14	孙志国, 任欣悦, 陈增茂, 等. 基于证据间相似性的协作频谱感知方法与性能分析[J]. 通信学报, 2020, 41 (12): 139- 147.
	SUN Z G , REN X Y , CHEN Z M , et al. Cooperative spectrum sensing method and performance analysis based on similarity between evidences[J]. Journal on Communications, 2020, 41 (12): 139- 147.
15	XIAO F Y . Multi-sensor data fusion based on the belief divergence measure of evidences and the belief entropy[J]. Information Fusion, 2019, 46, 23- 32. doi: 10.1016/j.inffus.2018.04.003
16	王旋, 狄鹏, 尹东亮. 基于Lance距离和信度熵的冲突证据融合方法[J]. 系统工程与电子技术, 2022, 44 (2): 592- 602.
	WANG X , DI P , YIN D L . Conflict evidence fusion method based on lance distance and credibility entropy[J]. Systems Engineering and Electronics, 2022, 44 (2): 592- 602.
17	YE F , BAI P , TIAN Y . An algorithm based on evidence theory and fuzzy entropy to defend against SSDF[J]. Journal of Systems Engineering and Electronics, 2020, 31 (2): 243- 251. doi: 10.23919/JSEE.2020.000002
18	YAO D G , YUAN S G , LV Z B , et al. An enhanced cooperative spectrum sensing scheme against SSDF attack based on Dempster-Shafer evidence theory for cognitive wireless sensor networks[J]. IEEE Access, 2020, 8, 175881- 175890.
19	WANG Y J , ZHANG K Z , DENG Y . Base belief function: an efficient method of conflict management[J]. Journal of Ambient Intelligence and Humanized Computing, 2019, 10 (9): 3427- 3437.
20	JOUSSELME A L , GRENIER D , BOSSE E . A new distance between two bodies of evidence[J]. Information Fusion, 2001, 2 (2): 91- 101.
21	DENG Y . Uncertainty measure in evidence theory[J]. Science China Information Sciences, 2020, 63, 210201.
22	MA L C , XIANG Y , PEI Q Q , et al. Robust reputation-based cooperative spectrum sensing via imperfect common control channel[J]. IEEE Trans.on Vehicular Technology, 2017, 67 (5): 3950- 3963.
23	HATA M . Empirical formula for propagation loss in land mobile radio services[J]. IEEE Trans.on Vehicular Technology, 1980, 29 (3): 317- 325.

算法	无MU	AF攻击	AB攻击	随机攻击	混合攻击
本文算法	适用	适用	适用	适用	适用
证据间相似性法	适用	适用	适用	适用	适用
双重可靠评估法	适用	适用	适用	适用	适用
Jousselme距离法	适用	适用	适用	适用	适用
BJS+信度熵法	适用	适用	适用	适用	适用
Lance+信度熵法	适用	失效	失效	适用	失效
信噪比权重法	适用	失效	失效	适用	失效
Dempster融合法	适用	失效	失效	适用	失效

[1]	Wenjuan REN, Zhanpeng YANG, Guangluan XU, Kun FU. Fusion calculation model of sea moving target identity confidence [J]. Systems Engineering and Electronics, 2023, 45(4): 1082-1089.
[2]	Kang LIU, Minghao HE, Jun HAN, Geng WANG. A high conflict evidence fusion method based on eigenvector and Jousselme distance [J]. Systems Engineering and Electronics, 2022, 44(7): 2175-2180.
[3]	Xuan WANG, Peng DI, Dongliang YIN. Conflict evidence fusion method based on Lance distance and credibility entropy [J]. Systems Engineering and Electronics, 2022, 44(2): 592-602.
[4]	Xin GUAN, Haotian YU, Xiao YI. Research on evidence independence and its influence on target recognition [J]. Systems Engineering and Electronics, 2022, 44(1): 192-198.
[5]	Shengnan YAN, Mingxin LIU. Distributed cooperative compressed spectrum sensing scheme based on support set fusion [J]. Systems Engineering and Electronics, 2020, 42(2): 466-472.
[6]	Liang WANG, Zhanyi LU, Zhuoyu LI. Condition assessment method of equipment based on rough sets and evidence theory [J]. Systems Engineering and Electronics, 2020, 42(1): 141-147.
[7]	Yuqi CHEN, Tingxue XU, Zhiqiang LI, Haijun LI. Dynamic reliability analysis of complex multi-state system based on evidence GO method [J]. Systems Engineering and Electronics, 2020, 42(1): 230-237.
[8]	SHEN Yan’an, ZHANG Junbiao. Equipment management performance assessment based on cloud model and evidence theory [J]. Systems Engineering and Electronics, 2019, 41(5): 1049-1055.
[9]	JI Wei, CHEN Qingqing, ZHENG Baoyu. Dual defense scheme for large-scale intrusion in cognitive radio networks [J]. Systems Engineering and Electronics, 2019, 41(10): 2352-2358.
[10]	WANG Wei, LIU Fuxian, XU Hao. Group argumentation model based on evidence theory [J]. Systems Engineering and Electronics, 2018, 40(3): 603-608.
[11]	JI Wei, LI Bingxing, ZHENG Baoyu. Distributed intelligent intrusion prevention scheme based on reputation and consensus [J]. Systems Engineering and Electronics, 2018, 40(3): 665-670.
[12]	GAO Xiaoyang, WANG Gang. Target recognition based on improved combination of temporal evidence sources [J]. Systems Engineering and Electronics, 2018, 40(12): 2629-2635.
[13]	LU Cheng, XU Tingxue, WANG Hong. State prediction method of radar seeker based on the unification of local relevance vector machine model [J]. Systems Engineering and Electronics, 2018, 40(1): 9-16.
[14]	XU Hao, XING Qinghua, WANG Wei. Integrated air target identification of friend or foe based on DST-IFS [J]. Systems Engineering and Electronics, 2017, 39(8): 1757-1764.
[15]	CHEN Yingchun, LI Ou, SUN Yu. Optimization algorithm for DS evidence theory based on energy modification and decision set reduction [J]. Systems Engineering and Electronics, 2017, 39(8): 1878-1885.

Cooperative spectrum sensing method against SSDF attacks based on composite entropy and evidence theory

RichHTML

PDF (PC)

Knowledge

Abstract

Cite this article

share this article

Figures/Tables 8

References 23

Related Articles 15

Recommended Articles

Metrics

Comments