Think of this as a 24/7 security guard for your computers and networks. It continuously watches what’s happening, looks for signs of break‑ins or suspicious behavior, and alerts your team before a small issue turns into a major cyber incident.
Organizations struggle to spot cyberattacks quickly enough across complex IT environments. Threat detection tools and processes continuously monitor systems, identify suspicious activity, and surface real incidents faster so teams can contain damage and reduce downtime and losses.
Primarily comes from high‑quality, domain‑specific security telemetry, curated threat intelligence, and deeply integrated workflows with SOC processes. Vendors with long histories in incident response, rich detection content, and ecosystem integrations (SIEM, EDR, SOAR, cloud platforms) have defensible advantages over generic monitoring tools.
Classical-ML (Scikit/XGBoost)
Time-Series DB
High (Custom Models/Infra)
High‑volume telemetry ingestion and storage, plus real‑time analysis latency across logs, network traffic, and endpoints; cost and performance of keeping long retention windows for forensic analysis.
Early Majority
This domain reflects mature, broadly adopted practices (log analysis, intrusion detection, anomaly detection) but vendors differentiate via detection depth, signal coverage (network, endpoint, cloud), threat intelligence quality, UX for analysts, and ability to reduce alert fatigue through smarter analytics and automation.