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Self-learning Anomaly Detection in Industrial Production

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Configuring an anomaly-based Network Intrusion Detection System for cybersecurity of an industrial system in the absence of information on networking infrastructure and programmed deterministic industrial process is challenging. Within the research work, different self-learning frameworks to analyze passively captured network traces from PROFINET-based industrial system for protocol-based and process behavior-based anomaly detection are developed, and evaluated on a real-world industrial system.
Request Code : ZLIBIO4476022
Categories:
Year:
2023
Publisher:
KIT Scientific Publishing
Language:
English
Pages:
226
ISBN 10:
3731512572
ISBN 13:
9783731512578
ISBN:
3731512572,9783731512578
Series:
Karlsruher Schriften zur Anthropomatik, 59

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