Objective
The WaterSAFE project addresses the growing threat of malicious attacks on water distribution Cyber-Physical Systems (CPS)an unprecedented risk to public health, safety, and critical infrastructure operations. While the integration of Information Technology with Operational Technology in water organizations has revolutionized the evolution of smart water systems, it has also exposed security vulnerabilities.
WaterSAFE introduces a groundbreaking CPS security-as-a-service solution for water distribution systems. Currently, CPS security solutions do not take into consideration the implications of cyber or physical attacks on system dynamics and controls. By leveraging state-of-the-art Digital Twin and machine learning technologies, WaterSAFE enables real-time simulation, detection, and analysis of the impacts of cyber-physical threats, marking a paradigm shift in CPS security analysis. This proposed system incorporates an Early Warning System for real-time anomaly detection in both cyber and physical states, offering advanced response tools for mitigating contamination incidents caused by cyber or physical attacks. Additionally, WaterSAFE offers interactive training platforms for water operators that facilitate enhancing critical skills for effective responses in real-world emergency scenarios.
WaterSAFE uses scientific results from the ERC SyG Water-Futures project on real-time water quality state estimation, machine learning for event diagnosis, CPS security, and contamination management, toward a proof-of-concept Minimum Viable Product (MVP), demonstrated in a small-scale testbed as well as large-scale living lab. This goes beyond existing solutions, which do not consider system dynamics or health impacts.
WaterSAFE will enable water utilities to implement stronger risk management, respond faster and more effectively to incidents, and subsequently meet EU regulations, fostering a cybersecurity culture within the water sector.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques.
- engineering and technologyenvironmental engineeringnatural resources managementwater management
- natural sciencescomputer and information sciencescomputer security
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Programme(s)
- HORIZON.1.1 - European Research Council (ERC) Main Programme
Funding Scheme
HORIZON-ERC-POC - HORIZON ERC Proof of Concept GrantsHost institution
1678 Nicosia
Cyprus