Self-learning Anomaly Detection in Industrial Production : Dissertations in Series (Dissertationen in Schriftenreihe)

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Title

Self-learning Anomaly Detection in Industrial Production : Dissertations in Series (Dissertationen in Schriftenreihe)

Subject

Industrielles Steuerungssystem; Netzwerksicherheit; Netzwerk-Intrusion-Detection-System; Anomalieerkennung; selbstlernend; Industrial Control System; Network Security; Network Intrusion Detection System; Anomaly Detection; self-learning

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.

Creator

Meshram, Ankush

Source

https://library.oapen.org/handle/20.500.12657/63682

Publisher

KIT Scientific Publishing

Date

2023

Contributor

Indah Fatma Silvi

Rights

https://creativecommons.org/licenses/by-sa/4.0/

Format

Pdf

Language

English

Type

Textbooks

Identifier

10.5445/KSP/1000152715
9783731512578

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