Research Article
Modern Detection Techniques of False Data Injection Attacks in V2X Communication: A Critical Analysis
@INPROCEEDINGS{10.1007/978-3-031-51849-2_5, author={Thejmeela Seetamonee and Girish Bekaroo}, title={Modern Detection Techniques of False Data Injection Attacks in V2X Communication: A Critical Analysis}, proceedings={Innovations and Interdisciplinary Solutions for Underserved Areas. 6th EAI International Conference, InterSol 2023, Flic en Flac, Mauritius, September 16-17, 2023, Proceedings}, proceedings_a={INTERSOL}, year={2024}, month={2}, keywords={False data injection (FDI) Vehicle-to-Everything (V2X) Connected and Autonomous Vehicles (CAVs) cyber-security modern detection techniques}, doi={10.1007/978-3-031-51849-2_5} }- Thejmeela Seetamonee
Girish Bekaroo
Year: 2024
Modern Detection Techniques of False Data Injection Attacks in V2X Communication: A Critical Analysis
INTERSOL
Springer
DOI: 10.1007/978-3-031-51849-2_5
Abstract
During the previous decade, renowned companies such as Tesla, Ford and Volkswagen have actively been researching and investing in the production of connected and automated vehicles (CAVs). The vehicle-to-everything (V2X) technology, which is used to operate CAVs, has recently gained considerable attention due to its various benefits such as improved road safety, energy efficiency and enhanced traffic efficiency on roads. A significant growth is expected in CAVs and V2X which will, however, be positively linked to an increase in the risk of cyber-attacks, notably, False Data Injection (FDI) attacks, due to their high connectivity. The aim of FDI in CAVs is to alter data and/or make CAVs unresponsive to the driver. The impact of these attacks is alarming due to the possibility of death, injury and major infrastructural damages. The ability of FDI attacks to modify or suppress data, such as speed, distance, acceleration and position of CAVs makes it even more critical to study FDI detection techniques. As such, this paper critically compares and analyses key techniques used to detect FDI attacks within V2X communication. As part of this study, five modern FDI detection techniques, notably, State Residuals-based detection, Data Fusion Algorithm, MFC-DI, History Trajectory Scheme and Machine Learning Approach were investigated in terms of their detection accuracy, time, reliability, adaptability to varying V2X environments and ability to detect new attacks.
