Detection of Malicious Nodes in MANETs using Analytical Model

Abstract

Mobile Ad hoc Networks (MANETs) is a kind of network composed of mobile devices distributed in a geographic area where there is a lack of fixed infrastructure or centralized administration. Nodes within communication range communicate directly, while those out of range make use of other nodes to forward the message to given destination. In MANETs packet dropping attacks have remarkable consequences among other threats. Malicious nodes drop received data or control messages instead of relaying them, thus by affecting the traffic in the network. Blackhole attacks imply malicious nodes dropping all the packets they receive. Grayhole attacks are similar but malicious nodes drop packets statistically by following a predetermined probability distribution. It should be emphasized that recognizing the actual cause(mobility, collision, errors, malicious behavior)for packet dropping in MANETs is still an open challenge, which is necessarily be addressed in order to reduce the number of false positives in IDS schemes. An Analytical model is introduced in order to distinguish between the legitimate packet dropping and malicious packet dropping behaviors. For that an enhanced windowing method is used for collecting the features from the network. From the features, the probabilities are to be calculated that are involved in analytical model. Based on the dropping probability that is estimated, concluded that the analyzed packet dropping node is malicious or legitimate by comparing with the predefined detection threshold.