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A Reflection-based Channel-State Group Fingerprint to Detect Intrusion Devices in ICS

  • Long Meng
  • , Xiangming Wang
  • , Shenjian Qiu
  • , Pengfei Liu
  • , Nanyi Deng
  • , Yang Liu
  • Xi'an Jiaotong University
  • Nanjing University of Aeronautics and Astronautics
  • Ltd.
  • Thermal Power Research Institute

科研成果: 书/报告/会议事项章节会议稿件同行评审

摘要

As the underlying network of the industrial control system (ICS), the fieldbus network can prevent attacks from the network. However, attackers can bypass physical defenses and physically connect intrusion devices to the fieldbus network to carry out various attacks. Many existing methods focus on detecting active intrusion devices by extracting their signal characteristics, but they struggle to detect inactive intrusion devices that are performing eavesdropping attacks without sending signals. This paper proposes a reflection-based channel-state group fingerprint to detect inactive intrusion devices. We theoretically analyze the reflection signals generated by the access of the intrusion device and observe that these reflection signals impact the signals of benign devices. Based on this, we extract the signal from a benign device before the intrusion and utilize it as a channel-state fingerprint. We detect inactive intrusion devices by analyzing the channel-state differences before and after intrusion. Additionally, we combine the channel-state fingerprints of multiple groups of devices to improve detection performance. The experimental results show that our method outperforms 99% in all detection metrics when detecting inactive intrusion devices.

源语言英语
主期刊名ICNSC 2024 - 21st International Conference on Networking, Sensing and Control
主期刊副标题Artificial Intelligence for the Next Industrial Revolution
出版商Institute of Electrical and Electronics Engineers Inc.
ISBN(电子版)9798350365221
DOI
出版状态已出版 - 2024
活动21st International Conference on Networking, Sensing and Control, ICNSC 2024 - Hangzhou, 中国
期限: 18 10月 202420 10月 2024

出版系列

姓名ICNSC 2024 - 21st International Conference on Networking, Sensing and Control: Artificial Intelligence for the Next Industrial Revolution

会议

会议21st International Conference on Networking, Sensing and Control, ICNSC 2024
国家/地区中国
Hangzhou
时期18/10/2420/10/24

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