Secure Cooperative Spectrum Sensing Strategy Based on Reputation Mechanism for Cognitive Wireless Sensor Networks

被引:22
作者
Luo, Xianquan [1 ]
机构
[1] Yango Univ, Coll Artificial Intelligence, Fuzhou 350015, Peoples R China
关键词
Sensors; Cascading style sheets; Reliability; Wireless sensor networks; Cognitive radio; Interference; Security; Cooperative spectrum sensing; reputation mechanism; cognitive wireless sensor networks; cognitive radio; MALICIOUS USER DETECTION; RADIO NETWORKS; ATTACK; SCHEME;
D O I
10.1109/ACCESS.2020.3009466
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Cooperative spectrum sensing can be regarded as a promising method to resolve the spectrum scarcity owing to achieving spatial diversity gain in cognitive radio sensor networks. However, the spectrum sensing data falsification attack launched by the malicious nodes will result in the wrong decision in the fusion center owing to the falsified observations. It will cause a serious security threat and degrade the decision making process. In this paper, we propose a secure cooperative spectrum sensing strategy based on reputation mechanism for cognitive wireless sensor networks to counter above kind of attack. The beta reputation model is applied to assign reputation value to cognitive sensor nodes according to their historical sensing behavior, and a dynamic trust evaluation scheme of cooperative spectrum sensing is established. In the final decision, the fusion center allocates a reasonable weight value according to the evaluation of the submitted observations to improve the accuracy of the sensing results. Simulation results support that our proposed strategy can weaken the impact of sensing data falsification attacks in cooperative sensing and outperform some traditional methods.
引用
收藏
页码:131361 / 131369
页数:9
相关论文
共 44 条
[11]  
Gupta M, 2016, 2016 IEEE INTERNATIONAL CONFERENCE ON RECENT TRENDS IN ELECTRONICS, INFORMATION & COMMUNICATION TECHNOLOGY (RTEICT), P609, DOI 10.1109/RTEICT.2016.7807894
[12]  
Han Y, 2012, IEEE VTS VEH TECHNOL
[13]   Distributed Error Correction of EKF Algorithm in Multi-Sensor Fusion Localization Model [J].
Hu, Fengjun ;
Wu, Gang .
IEEE ACCESS, 2020, 8 :93211-93218
[14]   An Efficient Group Recommendation Model With Multiattention-Based Neural Networks [J].
Huang, Zhenhua ;
Xu, Xin ;
Zhu, Honghao ;
Zhou, MengChu .
IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS, 2020, 31 (11) :4461-4474
[15]   Multimodal Representation Learning for Recommendation in Internet of Things [J].
Huang, Zhenhua ;
Xu, Xin ;
Ni, Juan ;
Zhu, Honghao ;
Wang, Cheng .
IEEE INTERNET OF THINGS JOURNAL, 2019, 6 (06) :10675-10685
[16]   ARC: Adaptive Reputation based Clustering Against Spectrum Sensing Data Falsification Attacks [J].
Hyder, Chowdhury S. ;
Grebur, Brendan ;
Xiao, Li ;
Ellison, Max .
IEEE TRANSACTIONS ON MOBILE COMPUTING, 2014, 13 (08) :1707-1719
[17]  
Hyder ChowdhurySayeed., 2011, Security and privacy in communication networks, P154
[18]   Optimization of Linear Cooperation in Spectrum Sensing Over Correlated Log-normal Shadow Fading Channels [J].
Jamali, V. ;
Reisi, N. ;
Ahmadian, M. ;
Salari, S. .
WIRELESS PERSONAL COMMUNICATIONS, 2013, 72 (03) :1691-1706
[19]   Malicious User Detection in a Cognitive Radio Cooperative Sensing System [J].
Kaligineedi, Praveen ;
Khabbazian, Majid ;
Bhargava, Vijay K. .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2010, 9 (08) :2488-2497
[20]   Catch Me if You Can: An Abnormality Detection Approach for Collaborative Spectrum Sensing in Cognitive Radio Networks [J].
Li, Husheng ;
Han, Zhu .
IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, 2010, 9 (11) :3554-3565