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Behavior prediction for industrial control system

  • Shen Wang*
  • , An Huang
  • , Zhongchuan Fu
  • *Corresponding author for this work
  • Harbin Institute of Technology

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

Abstract

While the Industrial control system(ICS) is making great progress for the society, it is facing a huge security risk at the same time. There are some methods like upgrading system and updating patches to protect the ICS, but they are inevitable lagging behind anyway. Byte-level is useful for network intrusion detection and does not need knowledge of the device to be detected. Based on the network data in the industrial control system, we propose an adaptive DBSCAN clustering method for extracting the control instructions in the data packet, and then learning these instructions with the n-gram model. According to received instructions, we are able to predict the next possible instruction. Whether the system is being attacked can be recommended by comparing the instruction that we forecast with the real instruction. Experiments show that the behavior prediction has high accuracy.

Original languageEnglish
Title of host publicationCommunications, Signal Processing, and Systems - Proceedings of the 2017 International Conference on Communications, Signal Processing, and Systems
EditorsQilian Liang, Min Jia, Jiasong Mu, Wei Wang, Xuhong Feng, Baoju Zhang
PublisherSpringer Verlag
Pages1953-1958
Number of pages6
ISBN (Print)9789811065705
DOIs
StatePublished - 2019
Event6th International Conference on Communications, Signal Processing, and Systems, CSPS 2017 - Harbin, China
Duration: 14 Jul 201716 Jul 2017

Publication series

NameLecture Notes in Electrical Engineering
Volume463
ISSN (Print)1876-1100
ISSN (Electronic)1876-1119

Conference

Conference6th International Conference on Communications, Signal Processing, and Systems, CSPS 2017
Country/TerritoryChina
CityHarbin
Period14/07/1716/07/17

Keywords

  • Adaptive dbscan
  • Behavior prediction
  • ICS
  • N-gram

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