A framework for resilient and secure spectrum sensing on cognitive radio networks

Cognitive radio networks have been envisaged to improve efficiency in accessing the frequency spectrum. However, these networks are prone to different kind of attacks and failures that can compromise the security and performance of licensed and unlicensed users. This work presents a framework for security and resilience in cognitive radio networks. As a showcase, this framework is applied to spectrum sensing functionality in order to assist its operation even in face to failures and attacks, such as primary user emulation ones. Differently from other proposals founded on specific and permanent device features, our framework provides flexibility and adaptation for detection and mitigation mechanisms considering best-efforts or real-time applications. Simulation results based on real traces provide evidences about the improvements achieved by our framework on spectrum sensing, even under primary user emulation attacks.