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Discover how AI-driven network observability can detect unknown and emerging threats across hybrid cloud and enterprise environments in this informative Tech Field Day presentation. Learn how cPacket applies machine learning and unsupervised anomaly detection to trillions of packets and billions of sessions to identify behavioral deviations, flag exfiltration attempts and lateral movement, and deliver real-time insights for proactive cybersecurity. Understand how the platform establishes baselines of normal behavior by location, application, and time patterns instead of using static thresholds, enabling detection of subtle anomalies like unusual session durations or unauthorized communication between network segments. See practical examples of how the system identifies both burst and slow-drift data exfiltration by monitoring session metrics, with insights aggregated into clear, actionable cards showing when, where, and why anomalies occurred. Explore the live, real-time view of network activity that allows security teams to drill down to packet-level details for thorough investigation, even without decrypting encrypted traffic. CTO Ron Nevo and Senior Director of Technical Marketing Andy Barnes demonstrate this comprehensive approach to network observability that significantly enhances proactive cybersecurity and incident response capabilities. Recorded at Security Field Day 13 in Santa Clara, CA on May 30, 2025.
