Table 13 Result analysis of the ablation study of the HDLID-ECSOA approach.

From: Leveraging hybrid deep learning with starfish optimization algorithm based secure mechanism for intelligent edge computing in smart cities environment

ToN-IoT Dataset

Approach

\(\:\varvec{A}\varvec{c}\varvec{c}{\varvec{u}}_{\varvec{y}}\)

\(\:\varvec{P}\varvec{r}\varvec{e}{\varvec{c}}_{\varvec{n}}\)

\(\:\varvec{R}\varvec{e}\varvec{c}{\varvec{a}}_{\varvec{l}}\)

\(\:{\varvec{F}}_{\varvec{M}\varvec{e}\varvec{a}\varvec{s}\varvec{u}\varvec{r}\varvec{e}}\)

DOA

97.22

89.47

84.94

86.42

SFOA

97.86

90.02

85.66

87.18

CNN-BiGRU-CRAM

98.53

90.76

86.28

87.83

HDLID-ECSOA

99.33

91.37

87.07

88.54

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