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    Day 1


The Fraunhofer Institute for Secure Information Technology realized a conceptual study to detect attacks and other anomalies by means of Machine Learning, and report those to production control based on monitoring of industrial plants.

  • Contrast to conventional Intrusion Detection Systems, this version does not need any type of defined attack patterns
  • The continuous evaluation of field bus-, sensor-, production and ERP-data is the basis of the anomaly detection
  • Means of autonomous process of machine learning, the system has the capability to recognize the standard range and raises an alarm by leaving it

Associated Speakers:

Thorsten Henkel

Director of Industrial Security Solutions

Fraunhofer SIT

Associated Talks:

04:00PM - Day 1

View Cognitive Security for the Industry 4.0 – Anomaly Detection and Integrity Protection

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