INTRUSION DETECTION SYSTEM FOR MANET USING MACHINE LEARNING AND STATE TRANSITION ANALYSIS

Nowadays the security of mobile adhoc networks is a major challenge because of its utilities in the extra ordinary situations. There are so many ways to employ the security to the adhoc network like intrusion detection systems (IDSs), key management, and trust and reputation management. Intrusion detection system implementation is our one of the major concerns. There are so many ways to implement and increase the security the MANET. This paper proposes the hybrid intrusion detection technique for the mobile adhoc networks that in turn employs the state transition analysis and SVM classification and genetic algorithm machine learning techniques to improve the efficiency and the security of the intrusion detection system.