Boston, May 8, 2019 – Host intrusion detection systems and network intrusion detection systems, which use pattern matching to detect threats, have reached their inflection point and given way to a new breed of detection solutions powered by machine learning: network threat analysis solutions. The unique pattern-of-life analysis that Darktrace is performing offers an intriguing alternative to the other machine-learning-powered network threat analysis solutions on the market.

This report offers Aite Group’s research findings of the Darktrace solution, covering—among other things—the mechanics of deployment, detection, autonomous response actions, pricing, architecture, and finally, communication and directionality of traffic. This research was collected through briefings with the vendor and from an interview with a Darktrace financial services customer located in Massachusetts during March of 2019.

This 20-page Impact Note contains six figures and four tables. Clients of Aite Group’s Cybersecurity service can download this report, the corresponding charts, and the Executive Impact Deck.

This report mentions Cambridge University, Cylance, Darktrace, Esri, Intruvert, Internet Security Systems, KnowBe4, Lawrence Livermore National Laboratory, Haystack Labs, National Security Agency, Naval Surface Warfare Center, Snort, Sourcefire, Suricata, and Top Layer.