Reputation based malicious node detection in OppNets

Routing and security management in Opportunistic Networks is challenging, where effective and secure forwarding of data delivery without any loss is not easy to guarantee. Packet dropping attacks are one of the most popular attacks that OppNets are exposed to. This paper presents an efficient malicious path, malicious node, and a packet dropping detection technique against selective packet dropping attacks. In our technique, we have developed a node by node packet dropping detection mechanism using the Merkle tree hashing technique. The result of detection is used to build trust and reputation for nodes, which are then used to detect malicious nodes. Simulation results show that the technique efficiently detects malicious paths, malicious nodes, and dropped packets. The results also show that with the increase of simulation time, node detection accuracy also increases as nodes have more time to establish reputation among nodes in the network. Results also show that the packet dropping rate drops over time, thus improving routing in OppNets.