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Table 9 Comparison between different existing methods and our proposed approach for UNSW-NB 15

From: Performance analysis of machine learning models for intrusion detection system using Gini Impurity-based Weighted Random Forest (GIWRF) feature selection technique

Proposed by ML methods used for IDS Accuracy(%) Recall/detection rate (DR) (%) F1 score (%)
Alazzam et al. (2020) Cosine-PIO DT 91.7 90
Khan et al. (2018) RF 75.65 76 73
Jing and Chen (2019) SVM 85.99
Kasongo and Sun (2020) DT 90.85 98.38 88.45
Meftah et al. (2019) SVM 82.11
Tama and Rhee (2019) GBM 91.31
Aboueata et al. (2019) SVM 92 92 91
Gu and Lu (2021) NB-SVM 93.75 94.73
Proposed approach GIWRF-DT 93.01 94.76 93.72