Table 8 Comparative analysis of the MDDoSFL-DRLFLO method with other models on the ToN-IoT dataset.

From: Mitigating distributed denial of service-based cyberattack in federated computing framework using deep reinforcement learning with frilled lizard algorithm

TON-IoT dataset

Classifier

\(\:Acc{u}_{y}\)

\(\:Pre{c}_{n}\)

\(\:Rec{a}_{l}\)

\(\:{F1}_{score}\)

MDDoSFL-DRLFLO

99.52

92.78

90.43

91.33

ANN Algorithm

99.44

91.67

90.03

90.58

TP2SF Method

98.84

85.70

89.97

90.10

Densely-Resnet

92.99

91.41

87.72

86.93

DFF Approach

97.35

88.48

86.99

87.54

DenseNet Method

98.57

88.64

89.05

89.86

XGBoost Model

98.30

86.10

89.46

88.07

NB

97.29

89.95

87.72

88.43

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