e-space
Manchester Metropolitan University's Research Repository

    Detecting message spoofing attacks on smart vehicles

    Ibrahim, Mohamad and Sohrabi Safa, Nader ORCID logoORCID: https://orcid.org/0000-0003-4897-0084 (2023) Detecting message spoofing attacks on smart vehicles. Computer Fraud & Security, 2023 (12). ISSN 1361-3723

    [img]
    Preview
    Accepted Version
    Available under License In Copyright.

    Download (1MB) | Preview

    Abstract

    The rapid proliferation of smart vehicles, particularly connected vehicles, has led to a rise in cyberthreats. Ensuring the security of associated equipment has become a pressing concern. This article presents an analysis of various machine learning models for detecting message spoofing attacks on smart vehicles. These types of attacks can pose a significant risk to the safety and security of smart vehicles, with dangers such as accidents, hijacking incidents and other severe consequences. The findings indicate the potential of machine learning models in detecting message spoofing attacks. And the results underscore the need for robust security measures to prevent message spoofing attacks on smart vehicles.

    Impact and Reach

    Statistics

    Activity Overview
    6 month trend
    91Downloads
    6 month trend
    98Hits

    Additional statistics for this dataset are available via IRStats2.

    Altmetric

    Repository staff only

    Edit record Edit record