RF Jamming Classification Using Relative Speed Estimation in Vehicular Wireless Networks

Kosmanos, Dimitrios; Karagiannis, Dimitrios; Argyriou, Antonios; Lalis, Spyros; Maglaras, Leandros

Abstract

Wireless communications are vulnerable against radio frequency (RF) interference which might be caused either intentionally or unintentionally. A particular subset of wireless networks, Vehicular Ad-hoc NETworks (VANET), which incorporate a series of safety-critical applications, may be a potential target of RF jamming with detrimental safety effects. To ensure secure communications between entities and in order to make the network robust against this type of attacks, an accurate detection scheme must be adopted. In this paper, we introduce a detection scheme that is based on supervised learning. e k-nearest neighbors (KNN) and random forest (RaFo) methods are used, including features, among which one is the metric of the variations of relative speed (VRS) between the jammer and the receiver. VRS is estimated from the combined value of the useful and the jamming signal at the receiver. e KNN-VRS and RaFo-VRS classification algorithms are able to detect various cases of denial-of-service (DoS) RF jamming attacks and differentiate those attacks from cases of interference with very high accuracy.

Citation

Kosmanos, D., Karagiannis, D., Argyriou, A., Lalis, S., & Maglaras, L. (2021). RF Jamming Classification Using Relative Speed Estimation in Vehicular Wireless Networks. Security and Communication Networks, 2021, Article 9959310. https://doi.org/10.1155/2021/9959310

• Journal Article Type: Article
• Acceptance Date: Aug 11, 2022
• Online Publication Date: Aug 26, 2021
• Publication Date: Aug 26, 2021
• Deposit Date: Nov 30, 2022
• Publicly Available Date: Nov 30, 2022
• Journal: Security and Communication Networks
• Print ISSN: 1939-0114
• Electronic ISSN: 1939-0114
• Publisher: Wiley
• Peer Reviewed: Peer Reviewed
• Volume: 2021
• Article Number: 9959310
• DOI: https://doi.org/10.1155/2021/9959310
• Keywords: Computer Networks and Communications; Information Systems
• Public URL: http://researchrepository.napier.ac.uk/Output/2963569