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  4. Anomaly detection in industrial networks using machine learning: A roadmap
 
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2017
Conference Paper
Titel

Anomaly detection in industrial networks using machine learning: A roadmap

Abstract
With the advent of 21st Century, we stepped into the fourth industrial revolution of cyber physical systems. There is the need of secured network systems and intrusion detection systems in order to detect network attacks. Use of machine learning for anomaly detection in industrial networks faces challenges which restricts its large-scale commercial deployment. ADIN Suite proposes a roadmap to overcome these challenges with multi-module solution. It solves the need for real world network traffic, an adaptive hybrid analysis to reduce error rates in diverse network traffic and alarm correlation for semantic description of detection results to the network operator.
Author(s)
Meshram, A.
Haas, Christian
Hauptwerk
Machine Learning for Cyber Physical Systems
Konferenz
Conference on Machine Learning for Cyber-Physical-Systems and Industry 4.0 (ML4CPS) 2016
Thumbnail Image
DOI
10.1007/978-3-662-53806-7_8
Language
English
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Fraunhofer-Institut für Optronik, Systemtechnik und Bildauswertung IOSB
Tags
  • machine learning

  • Industrial Network Security

  • anomaly detection

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