Detecting Selective Modification in Vehicular Edge Computing

Mobile Edge Computing can be used to realize the low latency requirements of vehicular networks. However, by compromising the road side units (RSUs), an adversary can introduce an extra delay leading to various problems such as the wastage of edge computing resources and disruption of navigational and safety functions. The compromised RSU can for instance deliberately corrupt the PHY layer payload of the packets to be transmitted to the vehicles. With this simple attack, the adversary would increase latency and through that effect, create serious disruptions. Such an attack can affect many critical delay sensitive applications such as collision avoidance. To detect the presence of such an adversary, we propose a trust based detection system in this paper. Each vehicle transmits a feedback packet about every RSU it has interacted with to a central trusted server. Using the feedback obtained from multiple vehicles, at regular intervals, an aggregated trust value for each RSU in the network is obtained and is compared with a threshold to classify the RSU as authentic or malicious. We also present a mechanism to detect the presence of malicious vehicles reporting false feedback in the network. Simulation results presented demonstrate the effectiveness of the proposed detection mechanism and the impact of the choice of adversary parameters on the detection system.