Darktrace has developed pioneering, autonomous machine learning software designed to detect and defend against cybersecurity threats from within computer networks.
Launched as an addition to its Enterprise Immune System technology in 2016, ‘Darktrace Antigena’ is a major step forward in the development of artificial intelligence and offers for the first time the possibility of a ‘self healing’ network. The technology learns and classifies actions so that it can recognise a threat, assess its magnitude and respond appropriately. The core technology uses machine learning techniques to analyse a network and make millions of probabilistic calculations using the data. Once it detects a threat, Antigena will calculate an effective but proportionate response to the attack, its algorithms generating a real-time action to protect the system. This might involve interrupting specific, highly suspicious connections, automatically reconfiguring a part of the network or temporarily freezing certain user privileges. These surgical actions only target the threatening behaviour, so business elsewhere on the system can continue as usual.
Antigena responds to a threat every 3 seconds and is being used by over 550 customers, including government agencies, international banks, healthcare providers and telecoms operators.
The nominated team members are: Matt Dunn, VP of Engineering; Matt Ferguson, Director of Development; Dave Palmer, Director of Technology; Alex Markham, Software Developer and Jack Stockdale, Chief Technology Officer.
MacRobert Award judge, Professor Nick Jennings CB FREng, on Darktrace:
“Antigena is a fantastic example of using machine learning in complex and constantly changing environments to protect valuable cyber assets. With minimal configuration, the software adapts to an organisation’s network and can offer automated detection and response to cyber-attacks. This degree of automation is essential for dealing with the volume, novelty and speed of modern cyber incidents. The ability to determine a proportionate response in real-time is a significant engineering innovation that extends the frontier of cyber security.”