Thales has developed Cybels Analytics, a tool that uses Artificial Intelligence (AI) and Big Data analytics technologies to detect complex cyber-attacks.
It will be unveiled at the 2020 edition of the International Cybersecurity Forum (FIC), the company said in a statement last week.
The platform combines real-time threat detection based on analysis of existing threats (Cyber Threat Intelligence) and proactive search for advanced and unprecedented cyberattacks ("cold" investigation or Hunting), thanks to artificial intelligence and graphic visualization modules. These capabilities reduce the time taken to detect advanced persistent threats from three months in average to just a few days, according to test results.
Cybels Analytics uses machine learning algorithms developed by Thales to detect abnormal situations based on huge volumes of heterogeneous data from multiple sources (network data, end point analysis, OT logging, etc.), helping to identify attack patterns and discover previously unknown threats. These algorithms, based on the principles of Thales TrUE AI, can be tailored to the specific needs of each business sector of activity by customers themselves via an easy-to-use graphical interface, the statement read.
Cybels Analytics can be integrated with an on-premise Security Operations Centre (SOC) or provided as a service in the cloud, enabling all the user's detection systems (SIEM, EDR, NIDS, etc.) to work together and complement one another. The platform is an important addition to Thales's cybersecurity offering, rounding out the range of managed services provided through its SOC network and supporting the Cybels Sensor trusted probe,which is accredited by France's National Agency for Information System Security (ANSSI). Cybels Analytics is also connected to the Thales Cyber Threat Intelligence service. By cross-referencing information about existing cyberthreats with an organisation's system logs, Cybels Analytics ensures acute, and exhaustive detection of untargeted attack, Thales claims.