Exploiting and defending trust models in cooperative spectrum sensing

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Abstract

Cognitive radios are currently presented as the solution to the ever-increasing spectrum shortage problem. However, their increased capabilities over traditional radios introduce a new dimension of security threats. Cooperative Spectrum Sensing (CSS) has been proposed as a means to protect cognitive radio networks from the well known security threats: Primary User Emulation (PUE) and Spectrum Sensing Data Falsification (SSDF). We demonstrate a new threat to trust-based CSS protocols, called the Rogue Signal Framing (RSF) intrusion. Rogue signals can be exploited to create the illusion of malicious sensors which leads to the framing of innocent sensors and consequently, their removal from the shared spectrum sensing. Ultimately, with fewer sensors working together, the spectrum sensing is less robust for making correct spectrum access decisions. To counter RSF, we introduce a new defense based on cluster analysis from analyzing the network’s Received Signal Strength (RSS) diversity, which demonstrates up to 95% damage reduction to sensor reputations.

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APA

Jackson, D., Zang, W., Gu, Q., & Cheng, W. (2014). Exploiting and defending trust models in cooperative spectrum sensing. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 8491, pp. 660–671). Springer Verlag. https://doi.org/10.1007/978-3-319-07782-6_59

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