Imagine a digital security guard that doesn't just look for known criminals but can spot a thief even if they've never seen their face before. It uses smart patterns to catch hackers who use AI to create new, invisible ways of breaking into systems. This keeps the lights on and the internet running by stopping attacks before they cause damage.
Current cybersecurity tools rely on old rules and signatures that cannot detect AI-generated malware. This leaves critical energy, telecom, and NGO infrastructures vulnerable to invisible attacks.
AI and machine learning algorithms and high TRL tools for detecting malware in software, firmware, and hardware.
If you are a grid operator dealing with invisible malware in hardware or firmware — this project developed AI-driven detection tools that protect critical energy infrastructures from downtime.
If you are a SOC provider dealing with AI-generated threats that bypass simple rules — this project developed high TRL tools that automate the detection of emerging malware.
If you are a non-profit dealing with limited security budgets and sophisticated attacks — this project developed cost-effective AI solutions to secure your digital infrastructure.
Based on available project data, specific pricing is not mentioned, but the project aims to provide solutions in a cost-effective way.
Yes, the project is designed for national-level cybersecurity infrastructures and critical sectors like energy and telecommunications.
Based on available project data, specific licensing terms are not provided, though it involves a consortium of 18 partners including 9 industry members.
The project period runs from 2025-10-01 to 2028-09-30.
The tools are specifically designed to be applied in real-life scenarios for private SOCs and CERTs/CSIRTs.
The project features a strong commercial orientation with a 50% industry ratio, comprising 9 industry partners (including 7 SMEs) and 8 partners across 8 countries. This balance between 3 universities and 5 research entities suggests a fast track from scientific discovery to industrial application.
Contact FERNUNIVERSITAT IN HAGEN in Germany
Contact us to connect with the PERUN consortium for early access to AI-malware detection tools.
