Lightweight trust model with machine learning scheme for secure privacy in VANET

Muhammad Haleem Junejo, Ab Al Hadi Ab Rahman, Riaz Ahmed Shaikh, Kamaludin Mohamad Yusof, Dileep Kumar, Imran Memon

Research output: Contribution to journalConference articlepeer-review

11 Citations (Scopus)
11 Downloads (Pure)


A vehicular ad hoc network (VANETs) is transforming public transport into a safer wireless network, increasing its safety and efficiency. The VANET consists of several nodes which include RSU (Roadside Units), vehicles, traffic signals, and other wireless communication devices that are communicating sensitive information in a network. Nevertheless, security threats are increasing day by day because of dependency on network infrastructure, dynamic nature, and control technologies used in VANET. The security threats could be addressed widely by using machine learning and artificial intelligence on the road transport nodes. In this paper, a comparison of trust and cryptography was presented based on applications and security requirements of VANET.

Original languageEnglish
Pages (from-to)45-59
Number of pages15
JournalProcedia Computer Science
Early online date3 Dec 2021
Publication statusPublished - 2021
Event18th International Learning and Technology Conference, L and T 2021 - Virtual, Online, Saudi Arabia
Duration: 28 Jan 2021 → …


  • Machine Learning
  • Trust Model

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