Self-learning Anomaly Detection in Industrial Production
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...
Furkejuvvon:
| Váldodahkki: | |
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| Materiálatiipa: | Online |
| Giella: | eaŋgalasgiella |
| Almmustuhtton: |
KIT Scientific Publishing
2023
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| Fáttát: | |
| Liŋkkat: | https://library.oapen.org/handle/20.500.12657/63682 |
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| _version_ | 1869527314099863552 |
|---|---|
| author | Meshram, Ankush |
| author_browse | Meshram, Ankush |
| author_facet | Meshram, Ankush |
| author_sort | Meshram, Ankush |
| collection | Directory of Open Access Books |
| 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. |
| format | Online |
| id | doab-20.500.12854ir-107952 |
| institution | Directory of Open Access Books |
| language | eng |
| publishDate | 2023 |
| publishDateRange | 2023 |
| publishDateSort | 2023 |
| publisher | KIT Scientific Publishing |
| publisherStr | KIT Scientific Publishing |
| record_format | ojs |
| spelling | doab-20.500.12854ir-1079522025-05-27T07:49:56Z 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 thema EDItEUR::U Computing and 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. 2023-07-26T22:26:11Z 2023-07-26T22:26:11Z 2023-06-26T14:36:24Z 2023 book https://library.oapen.org/handle/20.500.12657/63682 9783731512578 https://directory.doabooks.org/handle/20.500.12854/107952 eng Karlsruher Schriften zur Anthropomatik open access image/jpeg image/jpeg image/jpeg image/jpeg Attribution-ShareAlike 4.0 International Attribution-ShareAlike 4.0 International Attribution-ShareAlike 4.0 International Attribution-ShareAlike 4.0 International https://library.oapen.org/bitstream/handle/20.500.12657/63682/self-learning-anomaly-detection-in-industrial-production.pdf https://library.oapen.org/bitstream/20.500.12657/63682/1/self-learning-anomaly-detection-in-industrial-production.pdf https://library.oapen.org/bitstream/20.500.12657/63682/1/self-learning-anomaly-detection-in-industrial-production.pdf https://library.oapen.org/bitstream/20.500.12657/63682/1/self-learning-anomaly-detection-in-industrial-production.pdf KIT Scientific Publishing 10.5445/KSP/1000152715 10.5445/KSP/1000152715 68fffc18-8f7b-44fa-ac7e-0b7d7d979bd2 9783731512578 AG Universitätsverlage 224 open access |
| spellingShingle | Industrielles Steuerungssystem; Netzwerksicherheit; Netzwerk-Intrusion-Detection-System; Anomalieerkennung; selbstlernend; Industrial Control System; Network Security; Network Intrusion Detection System; Anomaly Detection; self-learning thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists Meshram, Ankush Self-learning Anomaly Detection in Industrial Production |
| title | Self-learning Anomaly Detection in Industrial Production |
| title_full | Self-learning Anomaly Detection in Industrial Production |
| title_fullStr | Self-learning Anomaly Detection in Industrial Production |
| title_full_unstemmed | Self-learning Anomaly Detection in Industrial Production |
| title_short | Self-learning Anomaly Detection in Industrial Production |
| title_sort | self learning anomaly detection in industrial production |
| topic | Industrielles Steuerungssystem; Netzwerksicherheit; Netzwerk-Intrusion-Detection-System; Anomalieerkennung; selbstlernend; Industrial Control System; Network Security; Network Intrusion Detection System; Anomaly Detection; self-learning thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists |
| topic_facet | Industrielles Steuerungssystem; Netzwerksicherheit; Netzwerk-Intrusion-Detection-System; Anomalieerkennung; selbstlernend; Industrial Control System; Network Security; Network Intrusion Detection System; Anomaly Detection; self-learning thema EDItEUR::U Computing and Information Technology::UY Computer science::UYA Mathematical theory of computation::UYAM Maths for computer scientists |
| url | https://library.oapen.org/handle/20.500.12657/63682 |
| work_keys_str_mv | AT meshramankush selflearninganomalydetectioninindustrialproduction |