British Military Gets A Defensive Cyber Security Platform

Computer scientists from the University of Southampton have collaborated with an incident solutions provider Riskaware to help defend UK military systems and networks from the rapidly growing cyber threats. The research partnership has created CyberAware Predict, which is a system that can predict both future cyber-attacks and the next steps of evolving attacks. 

Southampton University researchers shared expertise in cyber security and machine learning to enable the system to make predictions about the likely next steps of an evolving cyber attack against the monitored IT defence infrastructure. 

This process is based on network scans, real-time monitoring and threat intelligence and researchers from Southampton University Cyber Security Research Group have improved the capability with a £1m funding from the UK's Defence and Security Accelerator.   "In today's cyber threat landscape, attacks are becoming increasingly sophisticated and can develop over many consecutive stages, from reconnaissance to first intrusion, from privilege escalation to data exfiltration....CyberAware Predict aims to protect an IT defence infrastructure in a proactive way: by anticipating how and where cyber-attacks can target the infrastructure, and how they can evolve over time, the platform can help operators develop a more precise cyber risk awareness and take appropriate countermeasures in advance." said Dr Leonardo Aniello, Southampton University's project leader.

As the British miliary defence assets are being increasingly integrated with and reliant on the cyber space, the need arises to protect defence IT infrastructures from cyber-attacks to ensure security and continuity of critical operations. 

The capability to predict cyber threats in advance is a key enabler and presents a competitive advantage across all military domains and Riskaware's CyberAware platform includes visual analytics that enable organisations to understand and communicate current cyber risk, given analysis of real network vulnerabilities through cyber-attack prediction and simulation.

The aim is to help organisations identify how critical assets might be impacted by cyber-attacks, and ultimately facilitate the design of cost-effective cyber security controls that reduce cyber risk to acceptable levels. This new predictive capability relies on machine learning techniques that seamlessly integrates existing software tools and cyber threat intelligence (CTI) knowledge bases.

Riskaware:     Southampton University:     Southampton Univ. Cyber Security Group:
 

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