Detecting Forwarding Misbehavior In Clustered IoT Networks
Nalam Venkata Abhishek, Anshoo Tandon, Teng Joon Lim, Biplab Sikdar · 2018
Internet of Things (IoT) devices in clustered wireless networks can be compromised by compromising the gateway which they are associated with. In such scenarios, an adversary who has compromised the gateway can affect the network's performance by deliberately dropping the packets transmitted by the IoT devices. In this way, the adversary can actually mimic a bad radio channel. Hence, the affected IoT device has to retransmit the packet which will drain its battery at a faster rate. To detect such an attack, we propose a centralized detection system in this paper. It uses the uplink packet drop probability of the IoT devices to monitor the behavior of the gateway with which they are associated. The detection rule proposed is given by the generalized likelihood ratio test, where the attack probabilities are estimated using maximum likelihood estimation. Results presented show the effectiveness of the proposed detection mechanism and also demonstrate the impact of the choice of system parameters on the detection algorithm.