A Distributed Mix-Context-Based Method for Location Privacy in Road Networks

Preserving location privacy is increasingly an essential concern in Vehicular Adhoc Networks (VANETs). Vehicles broadcast beacon messages open form that contains information including vehicle identity, speed, location, and other headings. An adversary may track the various locations visited by a using sensitive transmitted beacons such as identity location. By matching used at locations, learns history of vehicle. This compromises driver. In existing research work, pseudonyms are place actual beacons. Pseudonyms should be changed regularly to safeguard vehicles. However, applying simple change does not always provide privacy. Existing schemes based on mix zones operate efficiently higher traffic environments but fail lower densities. this paper, we take problem diverse We propose new Crowd-based Mix Context (CMC) scheme provides well protection The pseudonym changing process utilizes context road direction number neighbors transmission range for anonymisation vehicles, adaptively updating vicinity. conduct formal modeling specification proposed High-Level Petri Nets (HPLN). Simulation results validate effectiveness CMC terms anonymisation, probability traceability, computation time (cost) effect vehicular applications.