Symantec has now officially started offering its machine learning-based threat detection tool to its customers, called the Targeted Attack Analytics.
According to details provided by Symantec, the Targeted Attack Analytics tool uses machine learning to discover attacks against corporate networks and it is the same technology that has been previously used by company’s research teams to discover a number of big cyber attacks, including the infamous Dragonfly 2.0.
The Symantec Targeted Attack Analytics tool was developed in cooperation between Symantec and investigators that were behind uncovering some of the most famous cyber threats like Stuxnet, Regin, Lazarus, SWIFT, and WannaCry.
The tool actually analyzes huge amounts of data as well as network telemetry to discover cyber attacks and according to Eric Chien, technical director of Symantec Security and Response, while both telemetry and data were previously available, the technology to analyze and code that data quickly was previously unavailable. With the Targeted Attack Analytics, the power of advanced machine learning has now been joined with intelligence generated by research teams to give customers the best chance to identify dangerous threats and take action.
“Symantec’s team of cyber analysts has a long history of uncovering the world’s most high-profile cyber-attacks and now their deep understanding of how these attacks unfold can be put to use by our customers without the need to employ a team of researchers,” said Greg Clark, Symantec CEO.
Targeted Attack Analytics uses advanced analytics and machine learning to help shorten the time to discovery on the most targeted and dangerous attacks and to help keep customers and their data safe.
According to Symantec, the Targeted Attack Analytics tool is available as a part of Symantec’s Integrated Cyber Defense Platform for Symantec Advanced Threat Protection (ATP) customers.