On insider misbehavior detection in cognitive radio networks

As the long-envisioned idea of cognitive radio becomes reality, an increasing number of security threats are being identified. Most of the security threats identified in the literature deal with external malicious users and provide solutions to mitigate the threats. In this article we elaborate on a newer kind of threat referred to as an insider attack in which cognitive users themselves misbehave in order to gain unauthorized or unfair access to spectrum resources. We show that insider attacks are comparatively easier to carry out in both licensed and unlicensed cognitive operations, and they can severely damage the expected system performance. We discuss how these threats can be mitigated, and outline the specific challenges that need to be addressed when designing a detection and mitigation strategy.