Spectra: Detecting Attacks on In-Vehicle Networks through Spectral Analysis of CAN-Message Payloads

Paper i proceeding, 2021

Nowadays, vehicles have complex in-vehicle networks that have recently been shown to be increasingly vulnerable to cyber-attacks capable of taking control of the vehicles, thereby threatening the safety of the passengers. Several countermeasures have been proposed in the literature in response to the arising threats, however, hurdle requirements imposed by the industry is hindering their adoption in practice. In this paper, we propose SPECTRA, a data-driven anomaly-detection mechanism that is based on spectral analysis of CAN-message payloads. SPECTRA does not abide by the strict specifications predefined for every vehicle model and addresses key real-world deployability challenges.