Probabilistic Misbehaviour Detection and Optimization in Delay Tolerant Network

Malicious and selfish behaviors represent a serious threat against routing in Delay/Disruption Tolerant Networks (DTNs). Due to the unique network characteristics, designing a misbehavior detection scheme in DTN is regarded as a great challenge. iTrust, a probabilistic misbehavior detection scheme, for secure DTN routing towards efficient trust establishment.. In this paper, we propose ant colony optimization for DTN routing towards efficient trust establishment. Ant Colony Optimization (ACO) with Optimized Link State Routing (OLSR) protocol to identify stable paths in between source and destination nodes. The basic idea of iTrust is introducing a periodically available Trusted Authority (TA) to judge the node’s behavior based on the collected routing evidences and probabilistically checking. We model iTrust as the Inspection Game and use game theoretical analysis to demonstrate that, by setting an appropriate investigation probability, TA could ensure the security of DTN routing at a reduced cost. To further improve the efficiency of the proposed scheme, we correlate detection probability with a node’s reputation, which allows a dynamic detection probability determined by the trust of the users. The extensive analysis and simulation results show that the proposed scheme substantiates the effectiveness and efficiency of the proposed scheme.