Date of Award

12-2019

Degree Name

MS in Computer Science

Department/Program

Computer Science

College

College of Engineering

Advisor

Bruce DeBruhl

Advisor Department

Computer Science

Advisor College

College of Engineering

Abstract

Intelligent vehicles are rapidly improving in functionality as they improve upon and incorporate new technologies. The addition of networking capabilities grants vehicles significant knowledge about the location and decisions of vehicles in the surroundings, and allows them to share perception information. However, adversarial listeners in the system may track vehicles by their communications resulting in a loss of user privacy. Past research has attempted to minimize privacy loss in single-radio environments through pseudonym changing schemes. We improved upon this research by comparing pseudonym schemes in a multi-radio environment.

Our simulation environment was created using the OMNeT++ networking and SUMO traffic simulators, with the Veins framework as an intermediary between the two. The OMNeT++ network software was extended using the INET framework to model WiFi traffic. This simulator was configured to test a variety of configurations for listener coverage and vehicle density. The data showed that the density-based pri vacy scheme offered improvement over the baseline timeout performance, while the blackout scheme posed no advantages.

Available for download on Sunday, December 11, 2022

Share

COinS