An edge-based smart network monitoring system for the Internet of Vehicles

Magaia, Naercio, Ferreira, Pedro and Pereira, Paulo Rogerio (2022) An edge-based smart network monitoring system for the Internet of Vehicles. IEEE International Conference on Communications 2022, Seoul, South Korea, 16–20 May 2022. Published in: IEEE International Conference on Communications (ICC). IEEE Xplore (Accepted)

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Abstract

The Internet of Vehicles (IoV) is the future of transportation. It will be present everywhere and will have a huge impact on our lives. However, there are plenty of aspects to consider while studying these networks, such as data dissemination, cybersecurity threats and vulnerabilities. For an IoV to work efficiently, data needs to spread through it efficiently. However, the dynamics of vehicular environments due to frequent node mobility and nodes' misbehavior poses many challenges to efficient data dissemination. Therefore, a deep learning-based monitoring system that is capable of detecting anomalies in the network and identifying known misbehavior is proposed. Performance evaluation shows that the monitoring system can identify well-known attacks with a very high success rate. Besides, the algorithm is also capable of detecting other types of misbehavior without labeling them.

Item Type: Conference Proceedings
Additional Information: © 2022 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords: Internet of Vehicles, Network Monitoring, Deep Learning, Edge
Schools and Departments: School of Engineering and Informatics > Informatics
Research Centres and Groups: Foundations of Software Systems
Subjects: Q Science > Q Science (General) > Q0300 Cybernetics > Q0325 Self-organizing systems. Conscious automata > Q0334 Artificial intelligence
T Technology > TK Electrical engineering. Electronics Nuclear engineering > TK5101 Telecommunication > TK5105.5 Computer networks
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Depositing User: Naercio Magaia
Date Deposited: 20 Jan 2022 11:31
Last Modified: 21 Jan 2022 16:03
URI: http://sro.sussex.ac.uk/id/eprint/103909

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