Anomaly Detection in Industrial Networks using Machine Learning: A Roadmap

被引:30
|
作者
Meshram, Ankush [1 ]
Haas, Christian [2 ]
机构
[1] Karlsruhe Inst Technol, Vis & Fus Lab, D-76131 Karslruhe, Germany
[2] Fraunhofer IOSB, Res Grp Securely Networked Syst, Fraunhoferstr 1, D-76131 Karslruhe, Germany
关键词
Machine Learning; Industrial Network Security; Anomaly Detection;
D O I
10.1007/978-3-662-53806-7_8
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
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.
引用
收藏
页码:65 / 72
页数:8
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