Maximum Mean Discrepancy Based Secure Fusion Strategy for Robust Cooperative Spectrum Sensing

2018 ◽  
Author(s):  
Shuai Yuan ◽  
Lei Li ◽  
Chunxiao Chigan
Keyword(s):  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Maximum Mean Discrepancy ◽  
Fusion Strategy

scholarly journals An SETM Algorithm for Combating SSDF Attack in Cognitive Radio Networks

2020 ◽  
Vol 2020 ◽  
pp. 1-9 ◽  
Author(s):  
S. Tephillah ◽  
J. Martin Leo Manickam
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Trust Management ◽  
Cooperative Spectrum Sensing ◽  
Radio Networks ◽  
Second Phase ◽  
Common Channel ◽  
Secondary Users ◽  
Management Algorithm ◽  
Different Types

Security is a pending challenge in cooperative spectrum sensing (CSS) as it employs a common channel and a controller. Spectrum sensing data falsification (SSDF) attacks are challenging as different types of attackers use them. To address this issue, the sifting and evaluation trust management algorithm (SETM) is proposed. The necessity of computing the trust for all the secondary users (SUs) is eliminated based on the use of the first phase of the algorithm. The second phase is executed to differentiate the random attacker and the genuine SUs. This reduces the computation and overhead costs. Simulations and complexity analyses have been performed to prove the efficiency and appropriateness of the proposed algorithm for combating SSDF attacks.

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