Behavioral Model to Detect Anomalous Attacks in Packet Transmission

Inside a network environment, packets is the most important in carrying data to perform communication. Such a circumstance is easy to be attacked by an intruder and perform eavesdropping which leads to data loss/duplication/redundancy. Comprehend speaking, packet dropping and modification are the two common attacks that can be easily launched by an adversary to disrupt communication in multi hop networks, specifically mobile ad hoc networks. Hence a remedial approach is proposed to compensate such attacks. A tree based approach is designed to designate the attack in order to identify packet droppers and modifiers. In this direction, it has been assumed that the mobile nodes continuously monitor the behaviors of the forwarding mobile nodes which may be neighbors to determine if their neighbors are misbehaving. To address this problem, a hierarchical method is proposed and detects malicious mobile nodes that drop or modify packets. Extensive analysis and simulations have been conducted to study the performance of attacks with respect to efficiency of