
This dataset is designed for evaluating Intrusion Detection Systems (IDS) in automotive networks. It features physically verified CAN traffic collected from multiple buses (C-CAN, P-CAN, and B-CAN). The dataset includes various attack scenarios such as Fuzzing, Spoofing, Replay, DoS, and UDS-based attacks, all executed in a real vehicle environment to ensure high fidelity. This dataset is provided as an appendix for the paper submitted to USENIX VehicleSec 2026.
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 0 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
