Table 7 Confusion matrix of the authorial antivirus and the state-of-the-art (%).

From: Antivirus applied to JAR malware detection based on runtime behaviors

Technique

 

Train

Test

M.

B.

M.

B.

Authorial Antivirus

M.

99.06 ± 0.25

0.94 ± 0.25

94.51 ± 1.83

5.49 ± 1.83

 

B.

3.72 ± 0.16

96.28 ± 0.16

10.79 ± 3.25

89.21 ± 3.25

Antivirus made by Lima et al. (2021),

M.

42.76 ± 49.24

57.24 ± 49.24

42.56 ± 49.07

57.44 ± 49.07

worst conf.6

B.

42.60 ± 49.51

57.40 ± 49.51

42.64 ± 49.45

57.36 ± 49.45

Antivirus made by Lima et al. (2021),

M.

94.27 ± 2.62

5.73 ± 2.62

93.42 ± 1.99

6.58 ± 1.99

best conf.6

B.

0.84 ± 1.65

99.16 ± 1.65

2.06 ± 1.77

97.94 ± 1.77

Antivirus made by Su

M.

74.86 ± 0.65

25.14 ± 0.65

74.86 ± 4.09

25.14 ± 4.09

et al.15

B.

16.86 ± 1.89

83.14 ± 1.89

16.86 ± 4.49

83.14 ± 4.49

Antivirus made by Vinayakumar

M.

97.63 ± 7.39

2.37 ± 7.39

96.60 ± 6.96

3.40 ± 6.96

et al.13

B.

0.46 ± 1.33

99.54 ± 1.33

3.12 ± 2.11

96.88 ± 2.11

Antivirus made by MANIATH, S

M.

95.02 ± 15.67

4.98 ± 15.67

88.54 ± 15.99

11.46 ± 15.99

et al.16

B.

34.14 ± 23.38

65.86 ± 23.38

35.52 ± 22.88

64.48 ± 22.88

Deep Learning made by WOZNIAK, M.

M.

70.00 ± 48.30

30.00 ± 48.30

70.00 ± 48.30

30.00 ± 48.30

et al.17

B.

70.00 ± 48.30

30.00 ± 48.30

70.00 ± 48.30

30.00 ± 48.30

Antivirus made by HOU, S.

M.

100.00 ± 0.00

0.00 ± 0.00

100.00 ± 0.00

0.00 ± 0.00

et al.18

B.

0.00 ± 0.00

100.00 ± 0.00

0.00 ± 0.00

100.00 ± 0.00

Antivirus made by HARDY,

M.

99.92 ± 0.22

0.08 ± 0.22

98.01 ± 2.03

1.99 ± 2.03

et al.19

B.

0.75 ± 2.02

99.25 ± 2.02

4.90 ± 2.30

95.10 ± 2.30

Antivirus made by KALASH, M.

M.

56.18 ± 2.25

43.82 ± 2.25

57.39 ± 5.97

42.61 ± 5.97

et al.20

B.

43.08 ± 15.14

46.92 ± 16.49

42.77 ± 15.12

47.23 ± 16.68

Deep Learning made by SANTOS,

M.

100.00 ± 0.00

0.00 ± 0.00

100.00 ± 0.00

0.00 ± 0.00

et al.22

B.

100.00 ± 0.00

0.00 ± 0.00

100.00 ± 0.00

0.00 ± 0.00