TY - JOUR
T1 - An Insider Attack Resistant Threshold Anonymous Traffic Violation Reporting Scheme for Fog-Assisted VANETs
AU - Yang, Yafang
AU - Zhang, Lei
AU - Zhao, Yunlei
AU - Choo, Kim Kwang Raymond
N1 - Publisher Copyright:
© 2004-2012 IEEE.
PY - 2025
Y1 - 2025
N2 - 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.
AB - 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.
KW - anonymity
KW - Fog-assisted VANETs
KW - report traceability
KW - traffic violation reporting
UR - https://www.scopus.com/pages/publications/105021225182
U2 - 10.1109/TDSC.2025.3628257
DO - 10.1109/TDSC.2025.3628257
M3 - 文章
AN - SCOPUS:105021225182
SN - 1545-5971
JO - IEEE Transactions on Dependable and Secure Computing
JF - IEEE Transactions on Dependable and Secure Computing
ER -