A stochastic approach for packet dropping attacks detection in mobile Ad hoc networks

A Mobile Ad hoc Network (MANET) is a dynamic network composed of mobile nodes that can communicate without relying on an existing infrastructure. In such decentralized environment, packet forwarding and other routing services are provided by network nodes cooperatively without any central administration. Most of existing Ad hoc routing protocols are based on the assumption that all network nodes are trustworthy. However, this assumption may be inconsistent when a malicious node decides to drop packets that are supposed to be forwarded in the aim of disrupting the routing services. Furthermore, the malicious node can change its behavior over time in order to appear as a legitimate node and still disrupting the network without being detected. To address this problem, we propose in this paper a fully decentralized mechanism that allows a node to monitor and detect neighbors that are malicious even if they have a changing behavior. Our mechanism is based on a Bernoulli Bayesian model for nodes' behavior classification and a Markov chain model for behavior evolution tracking. Performance analysis of numerical results obtained using NS2 simulations show an accurate detection of malicious nodes, which can be used to guarantee a reliable and secure packet forwarding among network nodes.