BATADAL 2.0

This dataset augments the information contained in the BATADAL dataset by combining process data (pertaining to a water distribution systems) with the network traces that characterise the information exchange within the industrial control system. This dataset is generated with DHALSIM.

Publications

• Erba, A., Murillo, A., Taormina, R., Galelli, S., Tippenhauer, N.O. (2024) On Practical Realization of Evasion Attacks for Industrial Control Systems. Proceedings of the 2024 Workshop on Re-design Industrial Control Systems with Security, October 14-18, Salt Lake City, UT. Best Paper Award.

BATADAL

For the BATtle of the Attack Detection ALgorithms (BATADAL), we generated various datasets used by the participants to develop attack detection algorithms (for water distribution systems). In particular, we developed two training and one testing datasets featuring a variety of attack scenarios.

Publications

• Taormina, R., Galelli, S., Tippenhauer, N.O., Salomon, E., Ostfeld, A, Eliades, D. … Ohar, Z. (2018) The battle of the attack detection algorithms: disclosing cyber attacks on water distribution networks. Journal of Water Resources Planning and Management, 144(8), 04018048.

IVS4EM

IVS4EM is a framework for developing and testing input variable (feature) selection algorithms. A key component of the framework is a dataset of 26 modelling problems, each sampled 30 times, for a total of 780 modelling exercises.

Publications

• Galelli, S., Humphrey, G.B., Maier, H.R., Castelletti, A., Dandy, G.C., Gibbs, M.S. (2014) An evaluation framework for input variable selection algorithms for environmental data-driven models. Environmental Modelling & Software, 62, 33-51.