クラウド
向けの、Netskope脅威対策

Netskope Behavior Analytics (UEBA)

Leverage machine learning (ML) behavior analysis across the rich metadata of cloud and web traffic, plus API inspection of managed apps and cloud services to detect anomalies, plus rich contextual sequential anomaly rules including the following:

• ML analysis of streaming and batch metadata for UEBA anomaly detection
• Unsupervised ML analysis developed and trained by the Netskope AI/ML team ready to use in production tenants
• Model development, training, and maintenance includes dynamic peer groups, decay factors, and correlation models
• Sequential anomaly rules include bulk uploads, downloads, deletes, rare events, proximity, failed logins, risky countries, and data exfiltration including between company and personal instances
• User Confidence Index (UCI) scoring determines user risk for events and alerts, plus UCI scores can drive policy actions such as step-up authentication
• AI/ML spans operations, data security, UEBA, malware detection, and URL filtering within Netskope.