Stochastic model: reCAPTCHA controller based co-variance matrix analysis on frequency distribution using trust evaluation and re-eval by Aumann agreement theorem against DDoS attack in MANET

The DDoS attack is more vulnerable attack in the self structured and infra structure less MANET environment. The bot net based flooding attack is very cheap and easy to implement. Many detection and prevention mechanisms has been proposed to avoid DDoS attack. Here we have proposed the stochastic model of covariance matrix analysis in which the entropy difference has been computed by the frequency distribution of rule metrics against the threshold entropy periodically which in turn difference is highest can be controlled by reCAPTCHA controller to defend against DDoS attack. The prevention mechanism by trust evaluation using clustering methodology used to identify the attacker and reduce the cost of detection mechanism. The Aumann agreement theorem based trust re-evaluation is also proposed in order to reduce the false positive and negative probabilities, such that the accuracy of the system is enhanced. Finally the nodes identified as attacker by their trust values will be evicted and rekeying has been done. The experimental analysis in NS2 with CAIDA dataset shows true positive rate and detection rate is high in the proposed mechanism.