Exploiting and defending trust models in cooperative spectrum sensing

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). In this paper, we demonstrate a new threat to CSS protocols that rely on sensor reputations, 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. The simulation experiments illustrate the impact of RSF intrusions which, in severe cases, shows roughly 40% of sensors removed. To counter the RSF’s impact on the cooperative spectrum sensing (CSS), we introduce a new defense based on cluster analysis and community detection from analyzing the network’s received signal strength (RSS) diversity. Tests show up to 95% damage mitigation to the integrity of sensor reputations, thus retaining the benefits of trust-based CSS protocols.