Chinese Journal on Internet of Things ›› 2023, Vol. 7 ›› Issue (2): 88-97.doi: 10.11959/j.issn.2096-3750.2023.00334

• Theory and Technology • Previous Articles     Next Articles

Time synchronization attack detection for industrial wireless network

Sichao ZHANG1,2,3,4, Wei LIANG1,2,3, Xudong YUAN1,2,3, Yinlong ZHANG1,2,3, Meng ZHENG1,2,3   

  1. 1 State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang 110016, China
    2 Key Laboratory of Networked Control Systems, Chinese Academy of Sciences, Shenyang 110016, China
    3 Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang 110169, China
    4 University of Chinese Academy of Sciences, Beijing 100049, China
  • Revised:2023-03-11 Online:2023-06-30 Published:2023-06-01
  • Supported by:
    The National Key Research and Development Program of China(2021YFB3301000);The National Natural Science Foundation of China(62022088);The National Natural Science Foundation of China(62273332)


High-precision time synchronization is the basis for ensuring the secure and reliable transmission of industrial wireless network (IWN).Delay attacks, as a class of time synchronization attacks which cannot be solved by cryptographic techniques, seriously threaten the secure operation of IWN.Firstly, based on the in-depth analysis on the time synchronization mechanisms of IWN, three-time synchronization attack models were proposed, including the one-way full life cycle delay attack, two-way full life cycle delay attack, and one-way non-full-life cycle delay attack.Stealthier delay attacks could be realized by the attack models under the premise that target nodes were not captured.Secondly, considering the problem that existing detection algorithms are difficult to detect stealthier delay attacks without obvious changes in time features, an attack detection algorithm based on a Bayesian model was proposed that extracts four representative features, including transmission rate, transmission delay, transmission success rate and time synchronization interval.In addition, in order to ensure the accuracy of the attack detection and classification in the presence of noise interference, the noise model of wireless channel was introduced to the Bayesian feature information matrix.Experimental results show that the proposed algorithm can effectively detect three kinds of attacks in the presence of noise.

Key words: industrial wireless network, time synchronization attack, delay attack, attack detection, Bayesian model

CLC Number: 

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