Spectra: Detecting Attacks on In-Vehicle Networks through Spectral Analysis of CAN-Message Payloads
Paper in proceedings, 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.

Author

Wissam Aoudi

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Nasser Nowdehi

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Magnus Almgren

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Tomas Olovsson

Chalmers, Computer Science and Engineering (Chalmers), Networks and Systems (Chalmers)

Proceedings of the ACM Symposium on Applied Computing

36th ACM Symposium On Applied Computing
Gwangju, South Korea,

Cyber Resilience for Vehicles - Cybersecurity for automotive systems in a changing environment - phase1 (CyReV)

VINNOVA, 2019-04-01 -- 2021-03-31.

RIOT: Resilient Internet of Things

Swedish Civil Contingencies Agency, 2019-01-01 -- 2023-12-31.

Resilient Information and Control Systems (RICS)

Swedish Civil Contingencies Agency, 2015-09-01 -- 2020-08-31.

KIDSAM: Knowledge and information-sharing in digital collaborative projects

VINNOVA, 2018-11-01 -- 2021-11-30.

VINNOVA, 2018-11-01 -- 2021-11-30.

Areas of Advance

Information and Communication Technology

Transport

Subject Categories

Other Engineering and Technologies not elsewhere specified

Vehicle Engineering

Embedded Systems

DOI

10.1145/3412841.3442032

More information

Created

12/10/2020