Attacker Placement for Detecting Vulnerabilities of Pseudonym Change Strategies in VANET

Saini, Ikjot; Ahmed, Sherif Saad; Jakel, Arunita

doi:10.1109/vtcfall.2018.8690701

Cited by 4 publications

(2 citation statements)

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“…In this article, we have compared and analyzed the effectiveness of the existing pseudonym changing schemes and evaluated their performance using the following two widely accepted performance metrics 10 , 11 : tracking success rate (TSR) and entropy of anonymity set size …”

Section: Introductionmentioning

confidence: 99%

“…The attackers can take advantage by having the information of PCS used by the vehicles. This knowledge benefits the attacker in the placement of the equipment 11 , 19 . If all the vehicles are following the same scheme in all the scenarios, various factors like traffic congestion, fixed time interval for the change, and intersection mix zones help the attacker to decide the most suitable location for placement for maximum coverage.…”

Section: Introductionmentioning

confidence: 99%

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Evaluating the effectiveness of pseudonym changing strategies for location privacy in vehicular ad‐hoc network

Saini

Saad

Jaekel

2019

Security and Privacy

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In a vehicular ad-hoc network, vehicles periodically broadcast safety messages to neighboring vehicles containing information about their identity, location, speed, and other relevant information. The time-critical nature of these messages means they are typically sent without encryption, which can compromise the privacy of the vehicle/driver. The use of pseudonyms, rather than the actual identity, has been suggested as a way to implement location privacy for drivers. However, such pseudonyms need to change frequently in order to prevent vehicle tracking. A pseudonym changing strategy (PCS) determines how frequently and under which conditions a vehicle should change its pseudonym. Many different PCS have been proposed in the literature over the last decade. However, there is a lack of a systematic analysis of the performance of these techniques, using a set of well-defined privacy metrics. In this article, we provide a thorough comparison of four main types of PCS, in terms of standard privacy metrics, and identify the advantages and limitations of each approach under different traffic conditions and attacker capabilities. The ultimate aim of this study is to help in the determination of the best PCS to use in different situations, to maximize the location privacy.

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