Pseudonym inference in cooperative vehicular traffic scenarios

Xu Chu, Na Ruan, Ming Li, Weijia Jia

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations


Vehicle platooning is a promising technique to enhance travel safety and road capacity. A common form of platooning is Cooperative Adaptive Cruise Control (CACC), where cars communicate their states with each other to maintain a constant gap between them. CACC can further reduce the headway between adjacent vehicles. However, the frequently broadcast safety messages with precise location and time information impose a significant threat to the location privacy of cars. Mix-zone based approaches are traditionally used to obfuscate vehicles' identities by mixing their pseudonyms. However, vehicles' movement is tightly coupled with each other inside a vehicular platoon, which introduces high predictability and spatial-temporal correlation for trajectories of vehicles. In this paper, we show how an adversary can exploit vehicles' platooning states to better infer their pseudonyms by observing their broadcast states before and after entering a mix-zone. We propose a novel attack strategy using a maximum likelihood estimator and expectation-maximization algorithm, and demonstrate the effectiveness of this attack through extensive simulations based on the real data from U.S. Highway 101. Our strategy achieves 30% higher inference accuracy compared with traditional non-platooning traffic scenarios. We also suggest a few possible approaches to mitigate such privacy threat in a platooning environment.

Original languageEnglish (US)
Title of host publication2018 IEEE Conference on Communications and Network Security, CNS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Print)9781538645864
StatePublished - Aug 10 2018
Event6th IEEE Conference on Communications and Network Security, CNS 2018 - Beijing, China
Duration: May 30 2018Jun 1 2018

Publication series

Name2018 IEEE Conference on Communications and Network Security, CNS 2018


Other6th IEEE Conference on Communications and Network Security, CNS 2018


  • Location privacy
  • mix-zone
  • vehicle platoon
  • vehicular ad-hoc networks (VANETs)

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Safety, Risk, Reliability and Quality


Dive into the research topics of 'Pseudonym inference in cooperative vehicular traffic scenarios'. Together they form a unique fingerprint.

Cite this