A HIDDEN MARKOVIAN METHOD TO SECURE INTRUSION DETECTION USING RANDOM CLUSTER HEAD ALGORITHM

WSN network is vulnerable to various security breaches. Depends on the application and their environment, it may vary dynamically and it is very unpredictable. In the network, each layer is prone to security breach. Designing Security measures for WSN is a challenging task. As we design more and more preventive measures for the attacks, number of attacks increases exponentially day by day. WSN has several limitations such as low energy, limited battery power, etc. So we need to consider these aspects as well while designing the system. In this paper, a new approach called Hidden Markovian Intrusion detection system is proposed which uses a new algorithm called Random Cluster Head selection. Experimental results show that the proposed model has achieved higher defense rate than any other game theoretic approaches.