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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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

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.

Original languageEnglish
Title of host publicationICNSC 2024 - 21st International Conference on Networking, Sensing and Control
Subtitle of host publicationArtificial Intelligence for the Next Industrial Revolution
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9798350365221
DOIs
StatePublished - 2024
Event21st International Conference on Networking, Sensing and Control, ICNSC 2024 - Hangzhou, China
Duration: 18 Oct 202420 Oct 2024

Publication series

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

Conference

Conference21st International Conference on Networking, Sensing and Control, ICNSC 2024
Country/TerritoryChina
CityHangzhou
Period18/10/2420/10/24

Keywords

  • Industrial Control System Security
  • Intrusion Device Detection
  • Signal Reflection

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