Identity trust management based on differential privacy for internet of vehicles

Abstract

Abstract Vehicle trust management is closely related to the identity security of intra-domain vehicles and has garnered widespread attention. However, there is a significant conflict between vehicle trust and identity privacy, which has led to the emergence of novel trust link attack issues. To address the problem, this paper proposes a vehicle identity trust management algorithm based on differential privacy, called DITDP. In DITDP, we first design an identity trust evaluation model based on D-S evidence, which is used to quantify vehicle trust values, including the direct trust, the recommended trust, and the aggregated trust. Then, we design the dynamic trust evaluation and identity privacy protection modules in DITDP. The dynamic trust evaluation module corrects conflict between vehicle trust components and can dynamically update vehicle trust values in the time domain. The identity privacy protection module achieves indistinguishable trust while ensuring the availability of trust value by using Differential privacy. Finally, the simulations verify that the DITDP algorithm performs well in terms of identity protection ability, trust availability, and other aspects.