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Privacy-Preserving Cloud-Based Road Condition Monitoring with Source Authentication in VANETs

  • Yujue Wang
  • , Yong Ding*
  • , Qianhong Wu
  • , Yongzhuang Wei
  • , Bo Qin
  • , Huiyong Wang
  • *此作品的通讯作者
  • Guilin University of Electronic Technology
  • State Key Laboratory of Cryptology
  • Science and Technology on Information Assurance Laboratory
  • Renmin University of China

科研成果: 期刊稿件文章同行评审

摘要

The connected vehicular ad hoc network (VANET) and cloud computing technology allows entities in VANET to enjoy the advantageous storage and computing services offered by some cloud service provider. However, the advantages do not come free, since their combination brings many new security and privacy requirements for VANET applications. In this paper, we investigate the cloud-based road condition monitoring (RCoM) scenario, where the authority needs to monitor real-time road conditions with the help of a cloud server so that it could make sound responses to emergency cases timely. When some bad road condition is detected, e.g., some geologic hazard or accident happens, vehicles on site are able to report such information to a cloud server engaged by the authority. We focus on addressing three key issues in RCoM. First, the vehicles have to be authorized by some roadside unit before generating a road condition report in the domain and uploading it to the cloud server. Second, to guarantee the privacy against the cloud server, the road condition information should be reported in ciphertext format, which requires that the cloud server should be able to distinguish the reported data from different vehicles in ciphertext format for the same place without compromising their confidentiality. Third, the cloud server and authority should be able to validate the report source, i.e., to check whether the road conditions are reported by legitimate vehicles. To address these issues, we present an efficient RCoM scheme, analyze its efficiency theoretically, and demonstrate the practicality through experiments.

源语言英语
文章编号8566002
页(从-至)1779-1790
页数12
期刊IEEE Transactions on Information Forensics and Security
14
7
DOI
出版状态已出版 - 7月 2019

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