Identify threats as they occur, not when they become public
Identifying ongoing threats to and within your networked environments is vital to maintaining compliance and data security. Darktrace uses machine learning and AI algorithms to detect and respond to cyber-threats across diverse digital environments, including cloud and virtualized networks, IoT and industrial control systems. The technology is self-learning, identifying threats in real time, including zero-days, insiders and stealthy, silent attackers.
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Powered by machine learning and AI algorithms, Darktrace's Enterprise Immune System technology iteratively learns a unique ‘pattern of life’ (‘self’) for every device and user on a network, and correlates these insights in order to spot emerging threats that would otherwise go unnoticed.
Machine learning & AI
Darktrace is powered by advanced, unsupervised machine learning, which is capable of learning what is normal and what is abnormal inside a network on an evolving basis, without using training data or customized models. This allows it to detect cyber-attacks that may not have been observed before, the ‘unknown unknowns’.
Real-time threat detection
The Enterprise Immune System can detect friend from foe in real time, identifying cyber-threats before they spread. Whether you face an insider threat or a long-term compromise, you are targeted with ransomware or a connected object is hacked, Darktrace sees the subtle indicators of abnormal activity, and defends your most critical systems.