Safety-Aware Location Privacy in VANET: Evaluation and Comparison

Abstract

VANET safety applications broadcast cooperative awareness messages (CAM) periodically to provide vehicles with continuous updates about the surrounding traffic. The periodicity and the spatiotemporal information contained in these messages allow a global adversary to track vehicle movements. Many privacy schemes have been proposed for VANET, but only few schemes consider their impact on safety applications. Also, each scheme is evaluated using inconsistent metrics and unrealistic vehicle traces, which makes comparing the actual performance of different schemes in the wild more difficult. In this paper, we aim to fill this gap and compare different privacy schemes not only in terms of the privacy gained, but also their impact on safety applications. A distortion-based privacy metric is initially proposed and compared with other popular privacy metrics showing its effectiveness in measuring privacy. A practical safety metric which is based on Monte Carlo analysis is then proposed to measure the QoS of two safety applications: forward collision warning and lane change warning. Using realistic vehicle traces, six state-of-the-art VANET privacy schemes are evaluated and compared in terms of the proposed privacy and safety metrics. Among the evaluated schemes, it was found that the coordinated silent period scheme achieves the best privacy and QoS levels, but fully synchronized silence among all vehicles is a practical challenge. The CAPS and CADS schemes provide a practical compromise between privacy and safety since they employ only the necessary silence periods to prevent tracking and avoid changing pseudonyms in trivial situations.