Journal of Communications and Networks

  • 제14권3호
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  • Pages.310-318
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  • 2012
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  • 1229-2370(pISSN)
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  • 1976-5541(eISSN)
한국통신학회 (The Korean Institute of Commucations and Information Sciences)
권호 표지

Intrusion Detection Scheme Using Traffic Prediction for Wireless Industrial Networks

  • Wei, Min (Department of Computer Science and Engineering, Konkuk University, Key Laboratory of Industrial Internet of Things & Networked Control, Ministry of Education Chongqing University of Posts and Telecommunications) ;
  • Kim, Kee-Cheon (Department of Computer Science and Engineering, Konkuk University)
  • 투고 : 2011.03.22
  • 심사 : 2012.04.09
  • 발행 : 2012.06.30
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초록

Detecting intrusion attacks accurately and rapidly in wireless networks is one of the most challenging security problems. Intrusion attacks of various types can be detected by the change in traffic flow that they induce. Wireless industrial networks based on the wireless networks for industrial automation-process automation (WIA-PA) standard use a superframe to schedule network communications. We propose an intrusion detection system for WIA-PA networks. After modeling and analyzing traffic flow data by time-sequence techniques, we propose a data traffic prediction model based on autoregressive moving average (ARMA) using the time series data. The model can quickly and precisely predict network traffic. We initialized the model with data traffic measurements taken by a 16-channel analyzer. Test results show that our scheme can effectively detect intrusion attacks, improve the overall network performance, and prolong the network lifetime.

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과제정보

연구 과제 주관 기관 : National Research Foundation of Korea (NRF)

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