An Emerging Anomaly Detection Technique to Diminish the Routing Misbehavior in Mobile Ad hoc Network (MANET)

Mobile ad hoc network does not have traffic concentration points such as gateway or access points which perform behavior monitoring of individual nodes. Therefore, maintaining the network function for normal nodes when other nodes do not route and forward correctly is a big challenge. This paper, address the behavior based anomaly detection technique inspired by the biological immune system to enhance the performance of MANET to operate despite the presence of misbehaving nodes. Due to its reliance on overhearing, the existing watchdog technique may fail to detect misbehavior or raise false alarms in the presence of ambiguous collisions, receiver collisions, and limited transmission power. In this present scheme uses intelligent machine learning techniques that learns and detects each node by false alarm and negative selection approach.