SSDF protection in cooperative spectrum sensing employing a computational trust evaluation algorithm

2010 ◽  
Author(s):  
Mohammad Akbari ◽  
Abolfazl Falahati
Keyword(s):  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Trust Evaluation ◽  
Computational Trust ◽  
Evaluation Algorithm

scholarly journals A Cooperative Spectrum Sensing Scheme Based on Extension Theory for Cognitive Radio Sensor Networks

2014 ◽  
Vol 8 (1) ◽  
pp. 64-70
Author(s):  
Sheng Ouyang ◽  
Pin Wan ◽  
Yonghua Wang ◽  
Liyuan Wang ◽  
Qinruo Wang
Keyword(s):  
Cognitive Radio ◽  
Sensor Networks ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Extension Theory ◽  
Fusion Center ◽  
Final Decision ◽  
Trust Evaluation ◽  
Cognitive Radio Sensor Networks ◽  
Dependent Function

This paper proposes a cooperative censoring spectrum sensing scheme based on dependent function of extension theory for Cognitive Radio Sensor Networks (CRSN). The scheme uses the dependent function of Extension theory to identify the presence or absence of the licensed user's (LU) signal, and then calculate the related degree through dependent function to identify the initial test results of licensed users, and then send these results to the fusion center. Use a trust evaluation scheme based on noise jamming and channel attenuation for each node, and then this trust evaluation result of each node is sent to the fusion center. The fusion center makes the final decision by the K-M rule. Simulation results show that the proposed scheme could improve the detect probability effectively.

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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