Automotive Security

A modern vehicle has more lines of code than the Facebook backend. While lines of code is not the only metric to judge the utility of software, we see how challenging automotive security has become. Modern vehicles are increasingly becoming more sophisticated with the integration of varied infotainment features, autonomous features, hybrid fuel sources. These features are nice to have in one's car and we want to secure them from adversary access. Hence, nowadays, automotive security is concerned about protecting the intra-vehicular network, nodes of the network (called ECUs) as well as inter-vehicular network. The latter is often approached through the lens of edge computing.

Following is the list of publications and projects by the lab in the Automotive domain:

H. Olufowobi, C. Young, J. Zambreno, and G. Bloom, “SAIDuCANT: Specification-Based Automotive Intrusion Detection Using Controller Area Network (CAN) Timing,” IEEE Transactions on Vehicular Technology, vol. 69, no. 2, pp. 1484–1494, Feb. 2020, doi: 10.1109/TVT.2019.2961344.

U. Ezeobi, H. Olufowobi, C. Young, J. Zambreno, and G. Bloom, “Reverse Engineering Controller Area Network Messages using Unsupervised Machine Learning,” IEEE Consumer Electronics Magazine, pp. 1–1, 2020, doi: 10.1109/MCE.2020.3023538.

C. Young, J. Zambreno, H. Olufowobi, and G. Bloom, “Survey of Automotive Controller Area Network Intrusion Detection Systems,” IEEE Design Test, vol. 36, no. 6, pp. 48–55, Dec. 2019, doi: 10.1109/MDAT.2019.2899062.

C. Young, H. Olufowobi, G. Bloom, and J. Zambreno, “Automotive Intrusion Detection Based on Constant CAN Message Frequencies Across Vehicle Driving Modes,” in Proceedings of the ACM Workshop on Automotive Cybersecurity, New York, NY, USA, 2019, pp. 9–14, doi: 10.1145/3309171.3309179.

H. Olufowobi, S. Hounsinou, and G. Bloom, “Controller Area Network Intrusion Prevention System Leveraging Fault Recovery,” in Proceedings of the ACM Workshop on Cyber-Physical Systems Security & Privacy, New York, NY, USA, 2019, pp. 63–73, doi: 10.1145/3338499.3357360.

H. Olufowobi et al., “Anomaly Detection Approach Using Adaptive Cumulative Sum Algorithm for Controller Area Network,” in Proceedings of the ACM Workshop on Automotive Cybersecurity, New York, NY, USA, 2019, pp. 25–30, doi: 10.1145/3309171.3309178.

H. Olufowobi and G. Bloom, “Chapter 16 - Connected Cars: Automotive Cybersecurity and Privacy for Smart Cities,” in Smart Cities Cybersecurity and Privacy, D. B. Rawat and K. Z. Ghafoor, Eds. Elsevier, 2019, pp. 227–240.

H. Olufowobi, G. Bloom, C. Young, and J. Zambreno, “Work-in-Progress: Real-Time Modeling for Intrusion Detection in Automotive Controller Area Network,” in 2018 IEEE Real-Time Systems Symposium (RTSS), Dec. 2018, pp. 161–164, doi: 10.1109/RTSS.2018.00030.

C. Young, J. Zambreno, and G. Bloom, “Towards a Fail-Operational Intrusion Detection System for In-Vehicle Networks,” Nov. 2016.