The Titans Of AI And The ML Arms Race In Cybersecurity - Aite Group’s Latest Report Finds That Machine Learning-Powered Cybersecurity Solutions Are Becoming Must-Haves For Threat Detection And Response

Signature-based detection systems have failed to detect attacks (while still inundating analysts with false positives) because their adversaries’ tactics, techniques, and procedures are always changing. To end this historical epoch of failure, the technology that vendors use to detect and prevent attacks must adapt to meet the evolving approaches of hackers. ML is powering the next evolution of these systems. Aite Group’s newest report, The Titans of AI and the ML Arms Race in Cybersecurity, explores the rollout of ML solutions to replace or augment legacy signature detection systems in businesses’ environments.

"This new report describes how ML is transforming the cybersecurity marketplace, ushering in a new breed of solutions capable of detecting the tactics and techniques of adversaries while reducing the systemic problem of alarm fatigue that legacy signature-based detection systems have caused over the last two decades," explains Alissa Knight, senior analyst at Aite Group.

This report profiles 14 cybersecurity vendors headquartered in the United States and Europe: Arcadia Data, Awake Security, Cequence Security, Cisco, Cybraics, Darktrace, ExtraHop, Kenna Security, KineticFuse, Lastline, SentinelOne, Shape Security, Symantec, and Vectra. It is the result of interviews with vendors whose global cybersecurity solutions across four product categories (network security, endpoint detection and response, monitoring, and vulnerability management) rely on ML models. Aite Group conducted the interviews between October 2018 and January 2019.