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Table 3 The frequency distribution of attack categories of the UNSW-NB15 dataset

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

Attack categories

Count

% (percentage)

Normal

93000

36.09

Generic

58871

22.85

Exploits

44525

17.28

Fuzzers

24246

9.41

DoS

16353

6.35

Reconnaissance

13987

5.43

Analysis

2677

1.04

Backdoor

2329

0.90

Shellcode

1511

0.59

Worms

174

0.07

Total

257673

100