Defense Against Objective Function Attacks in Cognitive Radio Networks

Cognitive radio (CR) is a technology for identifying opportunities using the “spectrum holes” for communication by cognition. Consequently, we can increase spectrum resource utilization rate with CR. However, it is cognition that causes an unprecedented challenge for cognitive radio networks, especially in security performance. Based on security problems existing in cognitive radios, we analyze Objective function attacks in detail. To counter this attack, we propose a multi-objective programming model, called MOP, which verifies all parameters tampered, so that attackers can not prevent CR from adapting to surroundings. Our simulation results indicate that theMOP model can defend Objective function attacks effectively. Thus, with the MOP model based on Particle swarm optimization (PSO), cognitive radio networks will obtain the optimum condition.