Reputation-Based Trust Management for Distributed Spectrum Sensing

2014 ◽  
pp. 255-264 ◽  
Author(s):  
Seamus Mc Gonigle ◽  
Qian Wang ◽  
Meng Wang ◽  
Adam Taylor ◽  
Eamonn O. Nuallain
Keyword(s):  
Spectrum Sensing ◽  
Trust Management ◽  
Distributed Spectrum Sensing

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.

Distributed Spectrum Sensing Using Low Cost Hardware

2015 ◽  
Vol 83 (1) ◽  
pp. 5-17 ◽  
Author(s):  
Stefan Grönroos ◽  
Kristian Nybom ◽  
Jerker Björkqvist ◽  
Juhani Hallio ◽  
Jani Auranen ◽  
...  
Keyword(s):  
Spectrum Sensing ◽  
Low Cost ◽  
Distributed Spectrum Sensing

Distributed Cooperative Spectrum Sensing Algorithm Based on Average Consensus

2015 ◽  
Vol 713-715 ◽  
pp. 1090-1093
Author(s):  
Yong Xiu Feng ◽  
Ai Qin Bao ◽  
Deng Yin Zhang
Keyword(s):  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Signal To Noise Ratio ◽  
False Alarm Probability ◽  
Consensus Algorithm ◽  
Noise Effect ◽  
Distributed Spectrum Sensing ◽  
Average Consensus ◽  
Deviation Criterion ◽  
Interaction Channel

The existing distributed spectrum sensing algorithms usually assume that the information in interaction channel is totally correct and did not consider noise effect. To solve these problems, a new distributed cooperative spectrum sensing scheme based on average consensus is investigated in this paper. Based on minimum mean square deviation criterion, we design an iterative matrix suitable for consensus algorithm with considering the noise of interaction channel. Simulation results show that the proposed method achieves better detection performance under noise effect of interaction channel and outperforms conventional scheme by 11% at-5dB signal to noise ratio (SNR) and 0.1 false alarm probability.

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