4.8 Article

Fuzzy-Based Trustworthiness Evaluation Scheme for Privilege Management in Vehicular Ad Hoc Networks

期刊

IEEE TRANSACTIONS ON FUZZY SYSTEMS
卷 29, 期 1, 页码 137-147

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TFUZZ.2020.3030490

关键词

Authentication; Vehicular ad hoc networks; Reliability; Big Data; Public key cryptography; Behavioral big data; fuzzy comprehensive strategy; mutual authentication; trustworthiness evaluation; VANETs

资金

  1. National Natural Science Foundation of China [U1836115, 61672295, 61922045, 61672290]
  2. Natural Science Foundation of Jiangsu Province [BK20181408]
  3. Foundation of StateKey Laboratory of Cryptology [MMKFKT201830]
  4. JiangsuKey Laboratory of BigData Security& Intelligent Processing, NJUPT [BDSIP1901]
  5. Peng Cheng Laboratory Project of Guangdong Province [PCL2018KP004]
  6. CICAEET fund
  7. PAPD fund
  8. Postgraduate Research & Practice Innovation Program of Jiangsu Province [KYCX20_0971]

向作者/读者索取更多资源

In this article, a fuzzy-based trustworthiness evaluation scheme for privilege management in VANETs is proposed to ensure the reliability of messages and the allocation of privileges by evaluating the behavioral big data of vehicles. The research results demonstrate that the proposed scheme performs well in terms of security and efficiency.
The vehicular ad hoc network (VANET) is a type of mobile wireless networks, where vehicles are allowed to broadcast a message to its neighbors and access data from other participants. However, how to guarantee the reliability of these broadcast messages and prevent malicious vehicles from accessing the private data of the VANETs is still an open problem to be solved. As a countermeasure, a fuzzy-based trustworthiness evaluation scheme for privilege management in VANETs is proposed in this article. In the proposed scheme, to ensure the result of trustworthiness is valid, mutual authentication with conditional anonymity between the evaluator and the vehicle to be evaluated is first employed. Then, based on the vehicle's behavioral big data, the trustworthiness of each vehicle is evaluated by utilizing the fuzzy theory. Note that the privilege of a vehicle and the reliability of the vehicle's messages are determined by its trustworthiness. Moreover, the mobility of vehicles is also considered in this article, since the location of a vehicle is not constant and the monitoring area of an road side unit is limited. The results of theoretical and experimental analyses demonstrate that the proposed scheme performs well in terms of security and efficiency.

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