Car hacking: attack & defense challenge 2020
This is the dataset provided and collected while "Car Hacking: Attack & Defense Challenge" in 2020. We are the main organizer of the competition along with Culture Makers and Korea Internet & Security Agency. We are very proud of releasing these valuable datasets for all security researchers for free.
The competition aimed to develop attack and detection techniques of Controller Area Network (CAN), a widely used standard of in-vehicle network. The target vehicle of competition was Hyundai Avante CN7.
Therefore, the dataset is a CAN network traffic of Avante CN7 including normal messages and attack messages. The dataset contains:
1) Preliminary round train/test dataset
2) Final round dataset of host's attack session
The preliminary round contains two status of the vehicle ― S: Stationary, D: Driving.
In the final round, only stationary status traffic was collected for safety reason.
All CSV files have same headers:
Timestamp: logged time in UNIX timestamp (unit: second)
Arbitration_ID: CAN identifier in hexadecimal
DLC: data length code (1-8)
Data: CAN data field that contains up to 8-byte of data in hexadecimal. All bytes are seperated by a space.
Class: "Normal" or "Attack"
SubClass: attack type (if Class is "Attack", one of "Flooding", "Spoofing", "Replay", or "Fuzzing"; if Class is "Normal", "Normal")
Normal: Normal traffic in CAN bus.
Attack: Injected attack CAN messages. Four types of attacks are included: Flooding, Spoofing, Replay, Fuzzing.
Flooding: Flooding attack aims to consume CAN bus bandwidth by sending a massive number of messages.
Spoofing: CAN messages are injected to control certain desired function.
Replay: Replay attack is to extract normal traffic at a specific time and replay (inject) it into the CAN bus.
Fuzzing: Random messages are injected to cause unexpected behavior of the vehicle.
Please cite our dataset's page and paper when you use this dataset as follows.
Hyunjae Kang, Byung Il Kwak, Young Hun Lee, Haneol Lee, Hwejae Lee and Huy Kang Kim. "Car Hacking and Defense Competition on In-Vehicle Network." Third International Workshop on Automotive and Autonomous Vehicle Security, 2021.
You can download the paper from NDSS 2021 site: https://www.ndss-symposium.org/ndss-program/autosec-2021/
Hyunjae Kang, Byung Il Kwak, Young Hun Lee, Haneol Lee, Hwejae Lee, Huy Kang Kim, February 3, 2021, "Car Hacking: Attack & Defense Challenge 2020 Dataset", IEEE Dataport, doi: https://dx.doi.org/10.21227/qvr7-n418
4. Dataset download
You can download this dataset from IEEE DataPort: https://dx.doi.org/10.21227/qvr7-n418
5. see also
Please see the page [HCRL/Datasets] to find out more in-vehicle IDS datasets or other datasets that we have.