This dataset contains manipulated outputs from the Tennesse Eastman Process (TEP), an anonymized chemical process.
To produce each manipulated output, the value of a single TEP feature modified for two hours. The subsequent TEP response is recorded.
In total, 286 manipulations are performed and recorded: each manipulation varies in (i) its magnitude, (ii) the pattern of the manipulation, and (iii) which TEP feature was manipulated.
Funding
This work is supported in part by the Secure and Private IoT initiative at Carnegie Mellon CyLab (IoT@CyLab) and by Mitsubishi Heavy Industries through the Carnegie Mellon CyLab partnership program; by the U.S. Army Research Office and the U.S. Army Futures Command under contract W911NF-20-D-0002; by DARPA under contract HR00112020006; and by the U.S. Department of Defense under contract FA8702-15-D-0002.
Publisher Statement
Attributions for ML-based ICS Anomaly Detection: From Theory to Practice.
Clement Fung, Eric Zeng, and Lujo Bauer.
In Proceedings of the 31st Network and Distributed System Security Symposium, February 2024.Date
2023-08-30
