An Opportunistic Network Routing Mechanism For Anti-False Trust Value

The uncertainty of the transmission between the transmission nodes makes it impossible to establish end-to-end connections in Opportunistic Networks (OppNets). Instead, a store-and-forward strategy can be employed. However, such loosely-knit routing paths depend heavily on the cooperation among participating nodes. Selfish or malicious behaviors of nodes impact greatly on the network performance. Therefore, the trust routing for opportunistic networks gains a lot of concerns all over the world.In this paper, we design and validate a dynamic trust management model for secure routing optimization. We propose the concept of incorporating social trust into the routing decision process and design an opportunistic network routing mechanism for anti-false trust value based on social attributes (ORTA). ORTA is based on the observation that nodes move around and contact each other according to their centralities, similarities, probability, and trust values. A node sharing more social attributes in social history record with the destination is more likely to travel close to the latter in the near future and should be chosen as the next-hop forwarder. Furthermore, social trust can be established based on an observed node's trustworthiness and its encounter history. Based on direct and recommended trust, those untrustworthy nodes will be detected and purged from the trusted list. Since only trusted nodes" packets will be forwarded, the selfish nodes have the incentives to well-behave again.In this paper, the simulation experiment platform ONE is used to carry out simulation experiments on the proposed routing mechanism, and the ORTA algorithm with the other two routing algorithms are compared and analyzed in the aspects of delivery ratio, delivery delay and delivery cost. Simulation evaluation demonstrates that ORTA is very effective in detecting selfish or even malicious nodes and achieving better performance.