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Artificial Intelligence and machine learning techniques are vital to automating the detection and analysis of cybersecurity and OT system incidents. However, a full understanding of the process being monitored, including its communications and assets, is needed to avoid deluging security teams with anomalous event alerts.

This session looks at how AI can be used to precisely identify anomalies in the OT process that are indicative of equipment failure, a cyberattack or a system problem.

A combination of process parameter deviation information, and rules that detect specific data and events from a stream of network traffic, make for a powerful threat hunting tool.

See a demonstration of process anomaly detection in action and learn how it can help you accelerate incident detection and response, safeguarding availability and cybersecurity.


  • Chris Grove, Technology Evangelist, Nozomi Networks
  • Scott Smith, Senior Product Owner, Nozomi Networks

Webpage: Asset Intelligence: Focus on the OT and IoT Incidents that Matter
Data Sheet: Nozomi Networks Asset intelligence
Webpage: Threat Intelligence: Detect Emerging OT and IoT Threats and Vulnerabilities
Data Sheet: Nozomi Networks Threat Intelligence