R&I Project Hub

The Dark Web is a haven for criminals. It has become a forum and marketplace for weapons, drugs, organs, illicit pornography, software exploits, stolen private data, passwords, credit card details, counterfeit products and money. Illegal services are offered, like phishing, cyber-attacks, murder and rape for hire and money laundering.

This ERC project pushes the boundary of reliable data-driven decision making in cyber-physical systems (CPS), by bridging reinforcement learning (RL), nonparametric estimation and robust optimization. RL is a powerful abstraction of decision making under uncertainty and has witnessed dramatic recent breakthroughs. Most of these successes have been in games such as Go - well specified, closed environments that - given enough computing power - can be extensively simulated and explored.

Incoming files present one of the most serious threats to every corporate network. Cyber attackers have the knowledge and resources to implement highly sophisticated attacks using various methods such as encrypted and distributed malware attacks, zero-day attacks and more. These are delivered via files which are introduced into the target network by various channels, including email, removable media, and web download. Malware attacks can create serious damage to the organization but current available defensive measures fail to provide any protection against such attack.

AERAS aims to develop a realistic and rapidly adjustable cyber range platform for systems and organisations in the critical healthcare sector, to effectively prepare stakeholders with different types of responsibility and levels of expertise in defending high-risk, critical cyber-systems and organizations against advanced, known and new cyber-attacks, and reduce their security risks.