GEM-CAN: Real-World CAN-Bus Attack Scenarios on an Autonomous Vehicle for Intrusion Detection 

This dataset provides labeled CAN-bus traffic captured from a GEM e6 autonomous vehicle under normal operation and controlled cyberattacks. It includes ~143K frames spanning nominal driving (~100K), DoS floods using ID 0x00000000 (~41K), and data-tampering injections targeting brake and steering functions (~1.3K). Each entry records timestamp, arbitration ID, DLC, payload bytes, and a Normal/Attack label, with metadata detailing attack windows, bus load, bitrate, and test conditions. Data were collected via PCAN-View/PCAN-USB on a closed track while the vehicle operated autonomously. The dataset provides real-vehicle evidence of availability and integrity attacks—supporting reproducible evaluation of lightweight automotive intrusion detection systems. 

 Link to Dataset: Link

Related publications:

o   Tavasoli, M., Sarrafzadeh, A., Karimoddini, A., Phuapaiboon, T., Khaleghi, M., & Tobias, D. (2025). GEM-CAN: Real-World CAN-Bus Attack Scenarios on an Autonomous Vehicle for Intrusion Detection [Data set]. Center for Regional and Rural Connected Communities (CR2C2). https://doi.org/10.5281/zenodo.17834776