Table 5.

All evaluation results of the CNN-based models for each f attack.

Dataset	Model	Accuracy	Precision	Sensitivity	Specificity	F1-Score	FPR
Honest + $f_1$ Attack (#1)	CNN	92.4 ± 3.04	99.71 ± 0.18	87.24 ± 4.72	99.67 ± 0.2	92.99 ± 2.64	0.33 ± 0.2
	CNN+SVM	96.6 ± 0.95	97.2 ± 0.7	96.06 ± 1.22	97.16 ± 0.72	96.62 ± 0.93	2.84 ± 0.72
	CNN+LR	97.15 ± 0.79	98.24 ± 0.7	96.14 ± 0.9	98.2 ± 0.72	97.18 ± 0.77	1.8 ± 0.72
	CNN+RF	97.08 ± 0.79	98.67 ± 0.68	95.63 ± 0.87	98.62 ± 0.71	97.12 ± 0.77	1.38 ± 0.71
	CNN+KNN	94.82 ± 0.78	99.71 ± 0.18	90.84 ± 1.24	99.68 ± 0.2	95.07 ± 0.71	0.32 ± 0.2
	CNN+DT	93.23 ± 0.63	92.92 ± 1.25	93.5 ± 0.78	92.98 ± 1.15	93.2 ± 0.66	7.02 ± 1.15
Honest + $f_2$ Attack (#2)	CNN	99.55 ± 0.12	99.81 ± 0.28	99.29 ± 0.45	99.81 ± 0.28	99.55 ± 0.12	0.19 ± 0.28
	CNN+SVM	99.74 ± 0.14	99.76 ± 0.26	99.72 ± 0.28	99.76 ± 0.26	99.74 ± 0.14	0.24 ± 0.26
	CNN+LR	99.67 ± 0.14	99.76 ± 0.37	99.58 ± 0.38	99.76 ± 0.36	99.67 ± 0.14	0.24 ± 0.36
	CNN+RF	99.83 ± 0.14	99.86 ± 0.29	99.81 ± 0.23	99.86 ± 0.28	99.83 ± 0.14	0.14 ± 0.28
	CNN+KNN	98.43 ± 0.43	98.86 ± 0.63	98.03 ± 0.81	98.85 ± 0.63	98.44 ± 0.43	1.15 ± 0.63
	CNN+DT	99.67 ± 0.22	99.81 ± 0.23	99.53 ± 0.42	99.81 ± 0.23	99.67 ± 0.22	0.19 ± 0.23
Honest + $f_3$ Attack (#3)	CNN	94.2 ± 2.17	99.86 ± 0.19	89.83 ± 3.29	99.83 ± 0.23	94.55 ± 1.91	0.17 ± 0.23
	CNN+SVM	98.24 ± 0.57	99.1 ± 0.61	97.43 ± 0.55	99.08 ± 0.62	98.26 ± 0.56	0.92 ± 0.62
	CNN+LR	97.96 ± 0.87	99.1 ± 0.55	96.89 ± 1.15	99.07 ± 0.57	97.98 ± 0.85	0.93 ± 0.57
	CNN+RF	98.74 ± 0.24	99.48 ± 0.59	98.04 ± 0.42	99.47 ± 0.59	98.75 ± 0.25	0.53 ± 0.59
	CNN+KNN	94.13 ± 1.85	99.9 ± 0.19	89.66 ± 2.94	99.9 ± 0.21	94.48 ± 1.63	0.1 ± 0.21
	CNN+DT	96.48 ± 0.29	96.25 ± 0.57	96.71 ± 0.44	96.27 ± 0.54	96.47 ± 0.29	3.73 ± 0.54
Honest + $f_4$ Attack (#4)	CNN	98.69 ± 0.92	97.91 ± 2.06	99.47 ± 0.32	97.99 ± 1.95	98.67 ± 0.95	2.01 ± 1.95
	CNN+SVM	99.12 ± 0.29	99.24 ± 0.61	99.01 ± 0.37	99.24 ± 0.6	99.12 ± 0.29	0.76 ± 0.6
	CNN+LR	99.31 ± 0.14	99.43 ± 0.41	99.2 ± 0.32	99.43 ± 0.41	99.31 ± 0.14	0.57 ± 0.41
	CNN+RF	99.6 ± 0.18	99.71 ± 0.18	99.48 ± 0.27	99.71 ± 0.18	99.6 ± 0.18	0.29 ± 0.18
	CNN+KNN	98.57 ± 0.67	97.72 ± 1.06	99.42 ± 0.36	97.77 ± 1.01	98.56 ± 0.69	2.23 ± 1.01
	CNN+DT	99.05 ± 0.21	99.14 ± 0.12	98.96 ± 0.32	99.14 ± 0.12	99.05 ± 0.21	0.86 ± 0.12
Honest +$f_5$ Attack (#5)	CNN	82.46 ± 4.1	82.09 ± 13.91	83.46 ± 3.95	83.98 ± 8.75	81.76 ± 6.71	16.02 ± 8.75
	CNN+SVM	82.08 ± 0.32	80.94 ± 1.47	82.86 ± 1.09	81.39 ± 0.92	81.87 ± 0.39	18.61 ± 0.92
	CNN+LR	83.2 ± 0.71	83.36 ± 0.99	83.14 ± 1.73	83.32 ± 0.51	83.23 ± 0.48	16.68 ± 0.51
	CNN+RF	83.32 ± 0.92	86.41 ± 0.99	81.42 ± 1.62	85.52 ± 0.74	83.82 ± 0.72	14.48 ± 0.74
	CNN+KNN	76.14 ± 0.35	75.71 ± 2.58	76.39 ± 1.63	76.05 ± 1.23	75.99 ± 0.61	23.95 ± 1.23
	CNN+DT	75.9 ± 1.78	75.52 ± 2.52	76.12 ± 1.88	75.74 ± 2.05	75.8 ± 1.86	24.26 ± 2.05
Honest + $f_6$ Attack (#6)	CNN	98.27 ± 0.46	98.15 ± 0.66	98.38 ± 0.65	98.16 ± 0.65	98.26 ± 0.46	1.84 ± 0.65
	CNN+SVM	97.24 ± 0.68	97.24 ± 0.95	97.25 ± 0.97	97.25 ± 0.92	97.24 ± 0.68	2.75 ± 0.92
	CNN+LR	97.98 ± 0.56	97.96 ± 0.56	98.01 ± 0.98	97.96 ± 0.54	97.98 ± 0.55	2.04 ± 0.54
	CNN+RF	98.46 ± 0.49	98.38 ± 0.79	98.53 ± 0.74	98.39 ± 0.77	98.45 ± 0.49	1.61 ± 0.77
	CNN+KNN	97.01 ± 0.56	97.01 ± 1.07	97.01 ± 0.75	97.02 ± 1.02	97 ± 0.56	2.98 ± 1.02
	CNN+DT	95.75 ± 0.97	95.77 ± 0.55	95.74 ± 1.49	95.77 ± 0.57	95.75 ± 0.94	4.23 ± 0.57