Energy-efficient location privacy preserving in vehicular networks using social intimate fogs

Gaolei Li, Qiaolun Zhang, Jianhua Li, Jun Wu*, Peng Zhang


研究成果: Article査読

5 被引用数 (Scopus)


Although the ways to protect vehicular location privacy have been actively studied in recent years, the locations of vehicles are frequently submitted for authentication during accessing location-based services (LBS), which makes it easier for attackers to launch attacks by threaten the location privacy of vehicles. Moreover, the rapid deployment of electric vehicles requires location privacy-preserving to be more energy-efficient. In this paper, we proposed a novel energy-efficient location privacy preserving (ELPP) scheme in vehicular networks using social intimate fogs (SIFs). ELPP is based on three novel techniques. First, ELPP deal with large bursts of LBS requests by transferring them to their SIF. The key insight is that computing efficiency for location privacy preserving can be gained at the price of some communication delay. Second, ELPP introduces a travel plan-based LBS content pre-caching mechanism, which enables quick and exible retrieval and distribution of the LBS contents. Third, to guarantee confidentiality, ELPP randomly encrypted the data by access control encryption. ELPP is deployable on existing devices, without modifying protocols in vehicular networks. We present an implementation case of ELPP and validate that it is energy-efficient, fast, and secure.

ジャーナルIEEE Access
出版ステータスPublished - 2018 7月 23

ASJC Scopus subject areas

  • コンピュータ サイエンス(全般)
  • 材料科学(全般)
  • 工学(全般)


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