More Anonymity through Trust Degree in Trust-Based Onion Routing

Trust-based onion routing employs users’ own trust to circumvent compromised onion routers. However, it runs a high risk of being deanonymized by the inference attacks based on a priori trust relationships. In this paper, we first observe that the onion routers with higher trust degrees (e.g., those that are trusted by more other users) are more effective in defending against the inference attacks. We therefore incorporate trust degree into trust-based onion routing. With a rigorous theoretical analysis, we devise an optimal strategy for router selection and an optimal routing algorithm for path selection. Both minimize the risk of deanonymization through inference without sacrificing the capability of evading compromised routers. Moreover, simulation-based experiments on top of realworld social networks confirm the effectiveness of the optimal router selection.