Table 6 Comparative outcome of MMDoWA-ARDL approach with existing methods20,34,35,36,37.

From: Mitigating malicious denial of wallet attack using attribute reduction with deep learning approach for serverless computing on next generation applications

Classifier

\(Accu_{y}\)

\({\text{Prec}}_{n}\)

\({\text{Reca}}_{l}\)

\(F_{{Measure}}\)

NB

95.13

92.82

97.09

94.99

DBN Model

94.01

97.01

95.00

97.56

SVM Method

99.05

97.34

90.11

91.20

DQSP Model

91.60

90.58

99.01

97.34

Deep Q-Network

90.79

98.34

91.30

91.69

DNN Algorithm

97.10

97.64

96.17

90.57

Inception-ResNet

90.59

92.22

92.79

95.01

CAPM

92.36

91.34

99.13

97.84

MAR

91.39

99.05

91.93

92.20

APT

97.88

98.24

96.94

91.26

MMDoWA-ARDL

99.39

99.39

99.39

99.39

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