Study On Optical Communications, Volume. 50, Issue 3, 23012501(2024)

Research on False Data Injection Attack Identification based on CNN-CBAM

Xianjun ZHOU... Ru WANG*, Hang LIU and Bo JIN |Show fewer author(s)
Author Affiliations
  • School of Electrical and Electronic Engineering, Hubei University of Technology, Wuhan 430068, China
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    Figures & Tables(10)
    Model and schematic diagram of FDIA
    The structure of CNN model
    The structure of CBAM
    FDIA position detection method
    The structure of IEEE14 node system
    6 F1values of standard error of dynamic noise in different environments
    FDIA detection accuracy of standard error of dynamic noise in different environments
    • Table 1. Standards for power testing of IEEE14 and IEEE118 node systems

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      Table 1. Standards for power testing of IEEE14 and IEEE118 node systems

      系统模型IEEE14IEEE118
      线路的数量20186
      量测值的数量19180
      注入节点量测值的数量870
      功率流测量值的数量11170
      不能测量的线路数量27
    • Table 2. Performance comparison of different networks in IEEE14 node system

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      Table 2. Performance comparison of different networks in IEEE14 node system

      网络结构网络层数精确率(%)召回率(%)F1(%)RACC(%)
      DNN391.2491.8091.5287.74
      492.9593.1993.0788.92
      592.5192.6992.6088.65
      691.4992.0891.7887.98
      CNN394.2495.6594.9495.60
      495.3496.7896.0596.70
      595.0196.4195.7096.30
      694.8795.9795.4296.00
      SSA-CNN396.2797.3396.7997.15
      496.5797.8297.1197.69
      597.1698.2397.6998.04
      697.0297.9397.4797.71
      CNN-CBAM397.3599.5299.4396.31
      497.9199.4899.5597.10
      598.8099.7699.7098.25
      698.1099.6399.6097.98
    • Table 3. Performance comparison of different networks in IEEE118 node system

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      Table 3. Performance comparison of different networks in IEEE118 node system

      网络结构网络层数精确率(%)召回率(%)F1(%)RACC(%)
      DNN391.9092.3492.1287.91
      492.4693.6793.0688.65
      592.5894.7993.6788.13
      693.0195.6294.3090.70
      CNN394.5493.3294.9088.73
      498.8898.4698.2992.66
      598.2898.6598.3392.35
      699.1498.4998.2490.79
      SSA-CNN396.8998.0797.4889.37
      497.6898.7998.2390.69
      598.4699.0098.7392.16
      699.5999.2899.4393.67
      CNN-CBAM397.8897.7797.8392.44
      499.4899.4499.4694.45
      5100.00100.00100.0095.94
      6100.00100.00100.0096.72
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    Xianjun ZHOU, Ru WANG, Hang LIU, Bo JIN. Research on False Data Injection Attack Identification based on CNN-CBAM[J]. Study On Optical Communications, 2024, 50(3): 23012501

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    Paper Information

    Category: Research Articles

    Received: Aug. 6, 2023

    Accepted: --

    Published Online: Jul. 19, 2024

    The Author Email: WANG Ru (314742910@qq.com)

    DOI:10.13756/j.gtxyj.2024.230125

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