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

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 IEEE14 IEEE118
线路的数量 20 186
量测值的数量 19 180
注入节点量测值的数量 8 70
功率流测量值的数量 11 170
不能测量的线路数量 2 7

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（%）
DNN	3	91.24	91.80	91.52	87.74
	4	92.95	93.19	93.07	88.92
	5	92.51	92.69	92.60	88.65
	6	91.49	92.08	91.78	87.98
CNN	3	94.24	95.65	94.94	95.60
	4	95.34	96.78	96.05	96.70
	5	95.01	96.41	95.70	96.30
	6	94.87	95.97	95.42	96.00
SSA-CNN	3	96.27	97.33	96.79	97.15
	4	96.57	97.82	97.11	97.69
	5	97.16	98.23	97.69	98.04
	6	97.02	97.93	97.47	97.71
CNN-CBAM	3	97.35	99.52	99.43	96.31
	4	97.91	99.48	99.55	97.10
	5	98.80	99.76	99.70	98.25
	6	98.10	99.63	99.60	97.98

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（%）
DNN	3	91.90	92.34	92.12	87.91
	4	92.46	93.67	93.06	88.65
	5	92.58	94.79	93.67	88.13
	6	93.01	95.62	94.30	90.70
CNN	3	94.54	93.32	94.90	88.73
	4	98.88	98.46	98.29	92.66
	5	98.28	98.65	98.33	92.35
	6	99.14	98.49	98.24	90.79
SSA-CNN	3	96.89	98.07	97.48	89.37
	4	97.68	98.79	98.23	90.69
	5	98.46	99.00	98.73	92.16
	6	99.59	99.28	99.43	93.67
CNN-CBAM	3	97.88	97.77	97.83	92.44
	4	99.48	99.44	99.46	94.45
	5	100.00	100.00	100.00	95.94
	6	100.00	100.00	100.00	96.72

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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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