Details of Research Outputs

TitleRisk Quantification of Privacy Management in Vehicular Ad Hoc Networks
Creator
Date Issued2022
Conference Name2022 IEEE Smartworld, Ubiquitous Intelligence & Computing, Scalable Computing & Communications, Digital Twin, Privacy Computing, Metaverse, Autonomous & Trusted Vehicles (SmartWorld/UIC/ScalCom/DigitalTwin/PriComp/Metaverse)
Source PublicationProceedings - 2022 IEEE SmartWorld, Ubiquitous Intelligence and Computing, Autonomous and Trusted Vehicles, Scalable Computing and Communications, Digital Twin, Privacy Computing, Metaverse (SmartWorld/UIC/ATC/ScalCom/DigitalTwin/PriComp/Metaverse)
ISBN979-8-3503-4655-8
Pages2358-2365
Conference Date15-18 December 2022
Conference PlaceHaikou, China
PublisherIEEE
Abstract

Vehicles participating in routing operations in vehicular ad hoc networks (VANETs) are required to periodically broadcast beacon messages. However, frequently broadcasting the vehicular information can pose a serious threat upon users' location privacy. While the exploitation of collective anonymity scheme on pseudonym change is an effective approach to protecting the location privacy of a target vehicle in VANETs, the exposure impact of the collective anonymity on privacy risk of a target vehicle has not been investigated yet. In this paper, we focus on improving anonymity level for a target vehicle in a collective anonymity scenario while achieving a high level of privacy exposure risk management. To achieve this, we first propose a pseudonym change scheme based on an assessment of the privacy exposure risk, aiming to manage and mitigate the privacy exposure risk of the target vehicle brought by exposed neighboring vehicles. Then we formulate an analytical model according to our proposed scheme in order to quantify the anonymity level of the target vehicle simultaneously updating pseudonyms with its neighbors. Simulation results show that our proposed scheme succeeds in promoting the size of anonymity set of the target vehicle with the growth in the number of its exposed neighboring vehicles. Meanwhile, with different setting parameters, our scheme retains effective performance compared to the random pseudonym change scheme.

Keywordcollective anonymity location privacy Privacy exposure risk pseudonym change VANETs
DOI10.1109/SmartWorld-UIC-ATC-ScalCom-DigitalTwin-PriComp-Metaverse56740.2022.00367
URLView source
Language英语English
Scopus ID2-s2.0-85168103819
Citation statistics
Document TypeConference paper
Identifierhttp://repository.uic.edu.cn/handle/39GCC9TT/11642
CollectionFaculty of Science and Technology
Corresponding AuthorLiu, Gang
Affiliation
BNU-HKBU UIC,Faculty of Science and Technology,Zhuhai,519087,China
First Author AffilicationFaculty of Science and Technology
Corresponding Author AffilicationFaculty of Science and Technology
Recommended Citation
GB/T 7714
Liu, Gang,Hou, Ricky Yuen Tan. Risk Quantification of Privacy Management in Vehicular Ad Hoc Networks[C]: IEEE, 2022: 2358-2365.
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