CarDS - Controller Area Network and Automotive Ethernet Realistic Data Set

Paper i proceeding, 2025

Intrusion Detection Systems (IDSs) serve as a crucial defense mechanism against cyberattacks targeting the In-Vehicle Network (IVN) of modern, interconnected vehicles. To develop and test new IDS approaches, researchers require realistic IVN data featuring real attacks on moving vehicles. To this end, this paper presents Controller Area Network and Automotive Ethernet Realistic Data Set (CarDS), a novel dataset targeting both the Controller Area Network (CAN) and Automotive Ethernet (AE) traffic of a modern, multi-domain and multi-protocol IVN. Existing datasets are often simulated or limited to basic IVN architectures consisting of only a single CAN bus. Additionally, there are no realistic datasets for AE, despite its growing importance in high-speed in-vehicle communication. CarDS addresses these limitations by providing a labeled, time-synchronized dataset of CAN and AE traces that includes both comprehensive benign profiles and sophisticated attacks. Our traces are captured from an electric vehicle from 2020 featuring a domain-oriented architecture comprising 10 internal CAN buses and 6 AE buses. Specifically, our dataset covers 9h 07m 09s of real IVN data and features 397,383,125 CAN and 180,604,377 AE messages distributed over different scenarios in 258 traces.