1st Edition

Trust Management in the Internet of Vehicles

    116 Pages 15 B/W Illustrations
    by Chapman & Hall

    116 Pages 15 B/W Illustrations
    by Chapman & Hall

    The Internet of Vehicles (IoV) is referred to as an efficient and inevitable convergence of the Internet of Things, intelligent transportation systems, edge / fog and cloud computing, and big data, all of which could be intelligently harvested for the cooperative vehicular safety and non-safety applications as well as cooperative mobility management. A secure and low-latency communication is, therefore, indispensable to meet the stringent performance requirements of the safety-critical vehicular applications. 

    Whilst the challenges surrounding low latency are being addressed by the researchers in both academia and industry, it is the security of an IoV network which is of paramount importance, as a single malicious message is perfectly capable enough of jeopardizing the entire networking infrastructure and can prove fatal for the vehicular passengers and the vulnerable pedestrians. 

    This book thus investigates the promising notion of trust in a bid to strengthen the resilience of the IoV networks. It not only introduces trust categorically in the context of an IoV network, i.e., in terms of its fundamentals and salient characteristics, but further envisages state-of-the-art trust models and intelligent trust threshold mechanisms for segregating both malicious and non-malicious vehicles. Furthermore, open research challenges and recommendations for addressing the same are discussed in the same too.

    1. Introduction  2. Trust Management Meets the Internet of Vehicles  3. Trust – IoV: A Distributed Trust Management System for Misbehavior Detection in the Internet of Vehicles  4. Towards Secure and Resource Efficient IoV Networks: A Hybrid Trust Management Approach  5. Conclusion 


    Adnan Mahmood possesses a PhD in Computer Science and is a Lecturer in Computing – IoT and Networking at the School of Computing, Macquarie University, Sydney, Australia. Before moving to Macquarie University, Adnan spent a considerable number of years in both the academic and research settings of the Republic of Ireland, Malaysia, Pakistan, and the People's Republic of China. His research interests include, but are not limited to, the Internet of Things (primarily, the Internet of Vehicles), Trust Management, Software-Defined Networking, and the Next Generation Heterogeneous Wireless Networks.

    Quan Z. (Michael) Sheng is a full Professor and Head of the School of Computing at Macquarie University, Sydney, Australia. Michael holds a PhD in Computer Science from the University of New South Wales (UNSW), Australia. His research interests include Service Computing, Distributed Computing, Internet Technologies, and the Internet of Things. He is a recipient of the A Miner Most Influential Scholar Award on IoT (2019), ARC Future Fellowship (2014), Chris Wallace Award for Outstanding Research Contribution (2012), and the Microsoft Fellowship (2003). Michael is ranked by Microsoft Academic as one of the Most Impactful Authors in Services Computing (i.e., top five all time).

    Wei Emma Zhang is a Lecturer in the School of Computer Science, the University of Adelaide, Australia and a Researcher in the promising paradigms of Information Retrieval, Natural Language Processing, and Text Mining. Wei obtained her PhD from the University of Adelaide and spent a half year in IBM Research, Australia as a full-time Intern. She further spent two and a half years at Macquarie University, Sydney as a Postdoctoral Researcher before joining the University of Adelaide.

    Sira Yongchareon is currently an Associate Professor in the Department of Computer Science and Software Engineering at Auckland University of Technology, New Zealand. He received his PhD and MIT degrees from the Swinburne University, Melbourne, Australia. His research interest is in Ubiquitous / Pervasive Computing, including AI / Machine Learning and Data Management for the Internet of Things, Ambient Intelligence, Human Activity Recognition, Wireless Sensing, and Mobile / Edge Computing in Intelligent Environments.