Boston, — 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 record of failure, the technology that vendors use to detect and prevent attacks must adapt to meet the evolving approaches of hackers. Machine learning (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.
Aite Group is a global research and advisory firm delivering advice on business, technology, and regulatory issues and their impact on the financial services industry. With expertise in banking, payments, insurance, wealth management, and the capital markets, the group guides financial institutions, technology providers, and consulting firms worldwide.