Time synchronization attack detection for industrial wireless network
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...
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| Format: | Article |
| Language: | zho |
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China InfoCom Media Group
2023-06-01
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| Series: | 物联网学报 |
| Subjects: | |
| Online Access: | http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2023.00334/ |
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| _version_ | 1841533829893849088 |
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| author | Sichao ZHANG Wei LIANG Xudong YUAN Yinlong ZHANG Meng ZHENG |
| author_facet | Sichao ZHANG Wei LIANG Xudong YUAN Yinlong ZHANG Meng ZHENG |
| author_sort | Sichao ZHANG |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-936f1dd0f07b40bdb3ee0c41debdd531 |
| institution | Kabale University |
| issn | 2096-3750 |
| language | zho |
| publishDate | 2023-06-01 |
| publisher | China InfoCom Media Group |
| record_format | Article |
| series | 物联网学报 |
| spelling | doaj-art-936f1dd0f07b40bdb3ee0c41debdd5312025-01-15T02:54:32ZzhoChina InfoCom Media Group物联网学报2096-37502023-06-017889759578253Time synchronization attack detection for industrial wireless networkSichao ZHANGWei LIANGXudong YUANYinlong ZHANGMeng ZHENGHigh-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.http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2023.00334/industrial wireless networktime synchronization attackdelay attackattack detectionBayesian model |
| spellingShingle | Sichao ZHANG Wei LIANG Xudong YUAN Yinlong ZHANG Meng ZHENG Time synchronization attack detection for industrial wireless network 物联网学报 industrial wireless network time synchronization attack delay attack attack detection Bayesian model |
| title | Time synchronization attack detection for industrial wireless network |
| title_full | Time synchronization attack detection for industrial wireless network |
| title_fullStr | Time synchronization attack detection for industrial wireless network |
| title_full_unstemmed | Time synchronization attack detection for industrial wireless network |
| title_short | Time synchronization attack detection for industrial wireless network |
| title_sort | time synchronization attack detection for industrial wireless network |
| topic | industrial wireless network time synchronization attack delay attack attack detection Bayesian model |
| url | http://www.wlwxb.com.cn/zh/article/doi/10.11959/j.issn.2096-3750.2023.00334/ |
| work_keys_str_mv | AT sichaozhang timesynchronizationattackdetectionforindustrialwirelessnetwork AT weiliang timesynchronizationattackdetectionforindustrialwirelessnetwork AT xudongyuan timesynchronizationattackdetectionforindustrialwirelessnetwork AT yinlongzhang timesynchronizationattackdetectionforindustrialwirelessnetwork AT mengzheng timesynchronizationattackdetectionforindustrialwirelessnetwork |