Selfish Attacks and Detection in Cognitive Radio Ad-Hoc Networks using Markov Chain and Game Theory

Cognitive radio is an opportunistic communication technology designed to help unlicensed users to utilize the maximum available licensed bandwidth. Cognitive radio has recently attracted a lot of research interest. However, little research has been done regarding security in cognitive radio, while much more work has been done on spectrum sensing and allocation problems. A selfish cognitive radio node can occupy all or part of the resources of multiple channels, prohibiting other cognitive radio nodes from accessing these resources. Selfish cognitive radio attacks deals with serious security problem like fake signal attack, Channel pre-occupation attack. These security problems they significantly degrade the performance of a cognitive radio network. In this proposal we identify the types of selfish attacks in cognitive radio ad-hoc networks and propose an easy and efficient selfish cognitive radio attack detection technique using Markov chain model and Game Theory. This technique is simple and reliable and can be well fitted for practical work in future work.