Denial of service (DoS) attacks detection in MANETs using Bayesian classifiers

Abstract

Mobile Ad hoc Networks (MANETs) are dynamic and self-organized networks composed of mobile wireless entities. The communications between nodes are multihop, and provided in a decentralized way without preexisting infrastructure. These characteristics make MANETs vulnerable to many types of Denial of Service (DoS) attacks, this including, Wormhole, Blackhole and Grayhole attack. This latter targets some reactive routing protocols in the aim of disrupting the forwarding process in the network. Grayhole attack occurs during the route discovery phase when a malicious node drops some of received packets. The watchdog is a well-known intrusion detection mechanism and usually used to detect this kind of attack. However, watchdogs are characterized by a relatively high rate of false alerts. In this paper, we propose a novel approach of watchdog based on two Bayesian filters: Bernoulli and Multinomial. We use these two models in a complementary manner to successfully detect the packet dropping attacks in mobile ad hoc networks. Based on simulation results, our filters prove that these attacks can be detected with a high rate of accuracy.