Self-learning Anomaly Detection in Industrial Production
- Author
- Meshram, Ankush
- Published
- [Place of publication not identified] : KIT Scientific Publishing, 2023.
- Physical Description
- 1 electronic resource (224 pages).
Access Online
- library.oapen.org , Open Access: OAPEN Library, download the publication
- library.oapen.org , Open Access: OAPEN Library: description of the publication
- Series
- Language Note
- English
- Restrictions on Access
- Open Access Unrestricted online access
- Summary
- 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.
- Subject(s)
- Other Subject(s)
- ISBN
- KSP/1000152715
- Collection
- OAPEN Library.
- Terms of Use and Reproduction
- Creative Commons https://creativecommons.org/licenses/by-sa/4.0/
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