A novel approach for malicious nodes detection in ad-hoc networks based on cellular learning automata

There are some fields in ad-hoc networks that are more highlighted these days, such as energy consumption, quality of service and security. Among these, security has been predominantly concerned in military, civil and educational applications. In security problem, suspect nodes detection or abnormal behavior nodes is one of the most important parts. We have addressed the malicious nodes detection problem in ad-hoc networks using special type of learning automata in an irregular network. We have used the irregular cellular learning automata to detect anomalies in two levels. We have also rigorously evaluated the performance of our approach by simulating it with MATLAB and Glomosim simulator and have compared our solution with a powerful similar learning automata-based protocol named LAID. The simulation results proofs that our approach is more promising.