RADAR: a Radio-based Analytics for Dynamic Association and Recognition of pseudonyms in VANETs

This paper presents RADAR, a tracking algorithm for vehicles participating in Cooperative Intelligent Transportation Systems (C-ITS) that exploits multiple radio signals emitted by a modern vehicle to break privacy-preserving pseudonym schemes deployed in VANETs. This study shows that by combining Dedicated Short Range Communication (DSRC) and Wi-Fi probe request messages broadcast by the vehicle, it is possible to improve tracking over standard de-anonymization approaches that only leverage DSRC, especially in realistic scenarios where the attacker does not have full coverage of the entire vehicle path. The experimental evaluation compares three different metrics for pseudonym and Wi-Fi probe identifier association (Count, Statistical RSSI, and Pearson RSSI), demonstrating that the Pearson RSSI metric is better at tracking vehicles under pseudonym-changing schemes in all scenarios and against previous works. As an additional contribution to the state-of-the-art, we publicly release all implementations and simulation scenarios used in this work [1].

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Publication Details

Published
2025-10-19
DOI
https://doi.org/10.1109/vtc2025-fall65116.2025.11310197
Primary Topic
Vehicular Ad Hoc Networks (VANETs)
Type
article
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article

RADAR: a Radio-based Analytics for Dynamic Association and Recognition of pseudonyms in VANETs

F. Valgimigli, Dario Stabili, Mirco Marchetti, Giovanni Gambigliani Zoccoli
Vehicular Ad Hoc Networks (VANETs)
article

RADAR: a Radio-based Analytics for Dynamic Association and Recognition of pseudonyms in VANETs

F. Valgimigli, Dario Stabili, Mirco Marchetti, Giovanni Gambigliani Zoccoli
article en

Abstract

This paper presents RADAR, a tracking algorithm for vehicles participating in Cooperative Intelligent Transportation Systems (C-ITS) that exploits multiple radio signals emitted by a modern vehicle to break privacy-preserving pseudonym schemes deployed in VANETs. This study shows that by combining Dedicated Short Range Communication (DSRC) and Wi-Fi probe request messages broadcast by the vehicle, it is possible to improve tracking over standard de-anonymization approaches that only leverage DSRC, especially in realistic scenarios where the attacker does not have full coverage of the entire vehicle path. The experimental evaluation compares three different metrics for pseudonym and Wi-Fi probe identifier association (Count, Statistical RSSI, and Pearson RSSI), demonstrating that the Pearson RSSI metric is better at tracking vehicles under pseudonym-changing schemes in all scenarios and against previous works. As an additional contribution to the state-of-the-art, we publicly release all implementations and simulation scenarios used in this work [1].

University of Modena and Reggio Emilia (IT)
Openalex Percentile: Top 66%
Vehicular Ad Hoc Networks (VANETs)
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