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oapen-20.500.12657-63682
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oapen-20.500.12657-636822023-06-27T04:10:33Z Self-learning Anomaly Detection in Industrial Production Meshram, Ankush Industrielles Steuerungssystem; Netzwerksicherheit; Netzwerk-Intrusion-Detection-System; Anomalieerkennung; selbstlernend; Industrial Control System; Network Security; Network Intrusion Detection System; Anomaly Detection; self-learning bic Book Industry Communication::U Computing & information technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists 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. 2023-06-26T14:36:24Z 2023-06-26T14:36:24Z 2023 book https://library.oapen.org/handle/20.500.12657/63682 eng Karlsruher Schriften zur Anthropomatik application/pdf Attribution-ShareAlike 4.0 International self-learning-anomaly-detection-in-industrial-production.pdf KIT Scientific Publishing 10.5445/KSP/1000152715 10.5445/KSP/1000152715 44e29711-8d53-496b-85cc-3d10c9469be9 59 224 open access
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OAPEN
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DSpace
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| language |
English
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| description |
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.
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| title |
self-learning-anomaly-detection-in-industrial-production.pdf
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| spellingShingle |
self-learning-anomaly-detection-in-industrial-production.pdf
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| title_short |
self-learning-anomaly-detection-in-industrial-production.pdf
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| title_full |
self-learning-anomaly-detection-in-industrial-production.pdf
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| title_fullStr |
self-learning-anomaly-detection-in-industrial-production.pdf
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| title_full_unstemmed |
self-learning-anomaly-detection-in-industrial-production.pdf
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| title_sort |
self-learning-anomaly-detection-in-industrial-production.pdf
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| publisher |
KIT Scientific Publishing
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| publishDate |
2023
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| _version_ |
1771297604335828992
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