Imagine a smart security guard for a city's power grid that doesn't just watch for intruders but predicts where they will strike next. It uses AI to automatically shut down the right doors and restart essential services so the lights stay on. It also lets different emergency teams share warnings instantly so everyone is ready before the attack hits.
Critical infrastructure operators struggle to respond to cyber attacks quickly enough to prevent service outages. They lack the tools to predict attacks and automate the recovery of essential business functions.
An AI-assisted security system featuring automated threat hunting, attack prediction tools, and a cyber training range for staff.
If you are an electricity grid operator dealing with unpredictable cyber attacks on power distribution — this project developed AI-assisted prediction and response tools that prioritize recovery based on business risk impact.
If you are a hospital network provider dealing with ransomware that freezes patient records — this project developed automation and orchestration mechanisms that ensure business continuity and faster recovery of critical health services.
If you are a railway logistics company dealing with supply chain disruptions from cyber incidents — this project developed a Resilience Cyber Range and serious games to train staff and test response plans before a real crisis occurs.
Based on available project data, no specific commercial pricing or cost models are provided as this is an EU-funded research project.
Yes, the project is designed for Operators of Essential Services (OES) and is being validated across three major sectors: Energy, Transport, and Health.
The project aims to create an open and sustainable solution to maximize the uptake of its results, though specific license types are not listed.
It uses REST API-based architecture and integrates Cyber Threat Intelligence (CTI) and User & Entity Behaviour Analytics (UEBA) to provide situational awareness.
The project period runs from 2022-07-01 to 2025-06-30, suggesting the final validated results will be ready by mid-2025.
The consortium is heavily industry-driven with 10 industrial partners (including 6 SMEs), representing a 59% industry ratio. This strong commercial presence, combined with 3 universities and 4 other entities across 6 countries, indicates the project is focused on practical application rather than pure theory.
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