MixGroup: Accumulative Pseudonym Exchanging for Location Privacy Enhancement in Vehicular Social Networks

Abstract

Vehicular social network (VSN) is envisioned to serve as an essential data sensing, exchanging and processing platform for the future Intelligent Transportation Systems. In this paper, we aim to address the location privacy issue in VSNs. In traditional pseudonym-based solutions, the privacy-preserving strength is mainly dependent on the number of vehicles meeting at the same occasion. We notice that an individual vehicle actually has many chances to meet several other vehicles. In most meeting occasions, there are only few vehicles appearing concurrently. Motivated by these observations, we propose a new privacy-preserving scheme, called MixGroup, which is capable of efficiently exploiting the sparse meeting opportunities for pseudonym changing. By integrating the group signature mechanism, MixGroup constructs extended pseudonym-changing regions, in which vehicles are allowed to successively exchange their pseudonyms. As a consequence, for the tracking adversary, the uncertainty of pseudonym mixture is accumulatively enlarged, and therefore location privacy preservation is considerably improved. We carry out simulations to verify the performance of MixGroup. Results indicate that MixGroup significantly outperforms the existing schemes. In addition, MixGroup is able to achieve favorable performance even in low traffic conditions.