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Table 14 Comparison analysis of CIC-IDS2017 dataset

From: Machine learning-based network intrusion detection for big and imbalanced data using oversampling, stacking feature embedding and feature extraction

SI. No.

Authors

Data balancing

Dimension reduction

Algorithm

Selected feature

Accuracy(%)

1

[30]

–

IGR+CR +ReF

PART

–

99.95 (Binary)

2

Our Proposal

RO

SFE-PCA

ET

10

99.95 (Binary)

3

[34]

–

t-SNE

RF

–

99.78

4

[53]

–

NTLBO

LR

22

97.00

5

[35]

–

EDFS

DT

–

98.80

6

[36]

–

IG+Ranking +Grouping

RF

22

99.86

7

[36]

–

IG+Ranking +Grouping

J48

52

99.87

8

[42]

–

–

DNN+ACO

–

98.25

9

[22]

SGM

–

CNN

–

99.85

10

Our Proposal

RO

SFE-PCA

DT

10

99.99

11

Our Proposal

RO

SFE-PCA

RF

10

99.99

12

Our Proposal

RO

SFE-PCA

ET

10

99.99