An Insider Attack Resistant Threshold Anonymous Traffic Violation Reporting Scheme for Fog-Assisted VANETs

Yafang Yang*, Lei Zhang, Yunlei Zhao, Kim Kwang Raymond Choo

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Traffic violation reporting schemes for fog-assisted vehicular ad hoc networks are generally designed to support traffic management centers (TMCs) in detecting traffic violations so that appropriate actions can be taken against the involved vehicle owners. However, there are ongoing challenges such as ensuring accuracy or accountability with minimal privacy dis closure (e.g., accurate and reliable detection of traffic violations without disclosing the contents of the incident, achieving identity authentication while protecting the privacy of reporters), and how to guarantee the reports are correctly processed complicate the design of such schemes. To address these challenges, we propose a threshold anonymous traffic violation reporting (TATVR) scheme under the assumptions that the fog nodes (i.e., roadside units) and the TMC are semi-trusted, and the number of colluding vehicles is limited. We then extend the TATVR scheme (i.e., extended TATVR or E-TATVR) that does not rely on these assumptions. We explain how TMC can process the received reports more efficiently using the proposed E-TATVR scheme. We also evaluate the security of both proposed schemes and demonstrate that they simultaneously support (strong) confidentiality, non-frameability, conditional unlinkability, unforgeability, and conditional anonymity. In particular, we show that both schemes guarantee strong confidentiality, and the E-TATVR scheme additionally supports report traceability.

Original languageEnglish
JournalIEEE Transactions on Dependable and Secure Computing
DOIs
StateAccepted/In press - 2025
Externally publishedYes

Keywords

  • anonymity
  • Fog-assisted VANETs
  • report traceability
  • traffic violation reporting

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