Improved Reputation of Soft Fusion Based on Cooperative Spectrum Sensing Defence SSDF Attacks

被引：0
|
作者：
Yang, Zhenling [1 ]
Chen, Yuebin [1 ]
Xing, Chuanxi [1 ]
Yang, Jiangfeng [1 ]
Zheng, Ting [1 ]
机构：
[1] Yunnan Minzu Univ, Sch Elect Informat Engn, Kunming 650500, Yunnan, Peoples R China
来源：
PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON COMMUNICATIONS, INFORMATION MANAGEMENT AND NETWORK SECURITY | 2016年 / 47卷
关键词：
cooperation spectrum sensing; covariance detection; soft decision fusion; reputation degrees; SSDF attack;
D O I：
暂无
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Aiming at the uncertain factors about behavior of cooperative spectrum sensing technologies, the data fusion center(DFC) receives sensing information from the cognitive user(CU) indiscriminately and make spectrum sensing data falsification(SSDF) attack of a malicious user(MU) using do harm to cooperative spectrum sensing. In this paper, an improved soft fusion algorithm based on reputation was presented. According to CU with different scope of reputation of use different updated guidelines and introduced time attenuation factor. We distribute weighting coefficient of CU based on the reputation to undermine SSDF influence and improved the accuracy of data fusion center. Simulations showed that the improve algorithm can keep the performance of soft fusion in the face of SSDF attacks and improve the security of cooperative spectrum sensing.
引用
收藏
页码：181 / 185
页数：5
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