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Title: Design and analysis of multimodel-based anomaly intrusion detection systems in industrial process automation
Authors: Zhou, Chunjie
Huang, Shuang
Xiong, Naixue
Yang, Shuang-Hua
Li, Huiyun
Qin, Yuanqing
Li, Xuan
Keywords: Anomaly intrusion detection
Hidden Markov model (HMM)
Industrial process automation
Multimodel
Security
Issue Date: 2015
Publisher: © IEEE
Citation: ZHOU, C. ... et al, 2015. Design and analysis of multimodel-based anomaly intrusion detection systems in industrial process automation. IEEE Transactions on Systems, Man, and Cybernetics: Systems, 45 (10), pp. 1345 - 1360
Abstract: Industrial process automation is undergoing an increased use of information communication technologies due to high flexibility interoperability and easy administration. But it also induces new security risks to existing and future systems. Intrusion detection is a key technology for security protection. However, traditional intrusion detection systems for the IT domain are not entirely suitable for industrial process automation. In this paper, multiple models are constructed by comprehensively analyzing the multidomain knowledge of field control layers in industrial process automation, with consideration of two aspects: physics and information. And then, a novel multimodel-based anomaly intrusion detection system with embedded intelligence and resilient coordination for the field control system in industrial process automation is designed. In the system, an anomaly detection based on multimodel is proposed, and the corresponding intelligent detection algorithms are designed. Furthermore, to overcome the disadvantages of anomaly detection, a classifier based on an intelligent hidden Markov model, is designed to differentiate the actual attacks from faults. Finally, based on a combination simulation platform using optimized performance network engineering tool, the detection accuracy and the real-Time performance of the proposed intrusion detection system are analyzed in detail. Experimental results clearly demonstrate that the proposed system has good performance in terms of high precision and good real-Time capability.
Description: This article is closed access.
Sponsor: The work is supported by the National Natural Science Foundation of China (No.61272204) and the Fundamental Research Funds for the Central Universities of China (HUST: No. 2013ZZGH006).
Version: Submitted for publication
DOI: 10.1109/TSMC.2015.2415763
URI: https://dspace.lboro.ac.uk/2134/19651
Publisher Link: http://dx.doi.org/10.1109/TSMC.2015.2415763
ISSN: 1083-4427
Appears in Collections:Closed Access (Computer Science)

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