Table 6 Ablation study results comparing the RAIHFAD-RFE method on the CIC-IDS-2017 dataset.

From: Modelling of hybrid deep learning framework with recursive feature elimination for distributed denial of service attack detection systems

CIC-IDS 2017 Dataset

Approach

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

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

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

\(\:{\varvec{F}1}_{\varvec{S}\varvec{c}\varvec{o}\varvec{r}\varvec{e}}\)

RFE

97.50

94.41

94.08

94.40

IOPA

98.20

95.16

94.79

95.03

LSTM-BiGRU

98.78

95.75

95.42

95.62

RAIHFAD-RFE

99.35

96.36

96.22

96.28