Self-learning Anomaly Detection in Industrial Production

• Päätekijä: Meshram, Ankush (auth)
• Aineistotyyppi: Elektroninen Kirjan osa
• Kieli: englanti
• Julkaistu: KIT Scientific Publishing 2023
• Sarja: Karlsruher Schriften zur Anthropomatik 59
• Aiheet: Maths for computer scientists; Industrielles Steuerungssystem; Netzwerksicherheit; Netzwerk-Intrusion-Detection-System; Anomalieerkennung; selbstlernend; Industrial Control System; Network Security; Network Intrusion Detection System; Anomaly Detection; self-learning
• Linkit: OAPEN Library: download the publication; OAPEN Library: description of the publication

Yhteenveto

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.

Ulkoasu

1 electronic resource (224 p.)

ISBN

KSP/1000152715

Pääsy

Open Access