Secure Sensing in Cognitive Radio Networks using Emitters Electromagnetic Signature

As Cognitive Radio Networks (CRN) gain in popularity as an extremely promising wireless technology that can alleviate the apparent spectrum scarcity and support innovative wireless applications; they will become bigger targets for hackers. Moreover, they will also be exposed to diverse security threats especially at the PHY-layer spectrum sensing module. Hence, security consideration is central in its development. Starting with overview of on-going research efforts in CRN security enhancement, this paper describes a PHY-layer attacker model that exploits the adaptability and flexibility of CRN. In thwarting this attack, we propose a waveform pattern recognition technique to identify emitters and detect camouflaging attacker by using the Electromagnetic Signature (EMS) of the transceiver. On the performance of the algorithm, our simulation results show that our approach is effective in mitigating denial-of-service threat and facilitating better radio spectrum utilization.