Performance comparison of timing-based anomaly detectors for Controller Area Network: a reproducible study
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Abstract (arXiv)
This work presents an experimental evaluation of the detection performance of eight different algorithms for anomaly detection on the Controller Area Network (CAN) bus of modern vehicles based on the analysis of the timing or frequency of CAN messages. This work solves the current limitations of related scientific literature, that is based on private dataset, lacks of open implementations, and detailed description of the detection algorithms. These drawback prevent the reproducibility of published results, and makes it impossible to compare a novel proposal against related work, thus hindering the advancement of science. This paper solves these issues by publicly releasing implementations, labeled datasets and by describing an unbiased experimental comparisons.
Key facts. Cited by 4 papers in the map (data through 14 Oct 2026). First posted on arXiv 10 Jul 2023.
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Citing papers per year: 2024: 2; 2025: 0; 2026: 2.
4 papers.
- 2024Graph Canvas for Controllable 3D Scene Generationcited by 11
- 2024Evaluating lightweight unsupervised online IDS for masquerade attacks in CANcited by 3
- 2026MIDS: Detecting Stealthy Masquerade and Tampering Attacks on CAN Bus via Bidirectional Mambacited by 0
- 2026CAN We Trust Your Results? A Cross-Dataset Study of Automotive IDS Evaluationcited by 0
- 2026CAN We Trust Your Results? A Cross-Dataset Study of Automotive IDS Evaluation29 Jun 2026
- 2026MIDS: Detecting Stealthy Masquerade and Tampering Attacks on CAN Bus via Bidirectional Mamba17 Jun 2026
- 2024Graph Canvas for Controllable 3D Scene Generation27 Nov 2024
- 2024Evaluating lightweight unsupervised online IDS for masquerade attacks in CAN19 Jun 2024