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Design and analysis of multimodel-based anomaly intrusion detection systems in industrial process automation

journal contribution
posted on 26.11.2015, 14:24 by Chunjie Zhou, Shuang Huang, Naixue Xiong, Shuang-Hua Yang, Huiyun Li, Yuanqing Qin, Xuan Li
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.

Funding

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).

History

School

  • Science

Department

  • Computer Science

Published in

IEEE Transactions on Systems, Man, and Cybernetics: Systems

Volume

45

Issue

10

Pages

1345 - 1360

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

Publisher

© IEEE

Version

SMUR (Submitted Manuscript Under Review)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

09/01/2015

Publication date

2015-04-08

Notes

This article is closed access.

ISBN

2168-2216

ISSN

2168-2232

Language

en