Performance Analysis of Intrusion Detection Systems Using a Feature Selection Method on the UNSW-NB15 Dataset

Computer Science

• Feature Selection 100%
• Intrusion Detection System 100%
• Performance Analysis 100%
• Machine Learning 40%
• Extreme Gradient Boosting 40%
• Decision Trees 40%
• Intrusion Prevention Systems 40%
• Binary Classification 40%
• Detection Accuracy 20%
• Artificial Neural Network 20%
• Machine Learning Technique 20%
• Critical Aspect 20%
• Feature Space 20%
• Machine Learning Approach 20%
• Intrusion Detection 20%
• Network Intrusion Detection System 20%
• High Dimensional Data 20%
• Computer Network Intrusion 20%
• Feature Reduction 20%
• Classification Scheme 20%
• Support Vector Machine 20%
• Multiclass Classification 20%
• Logistic Regression 20%
• Feature Extraction 20%
• Classification Process 20%
• Computer Network 20%
• False Positive Rate 20%

Keyphrases

• UNSW-NB15 Dataset 100%
• High-dimensional Data Space 20%
• Intrusion Datasets 20%
• UNSW-NB15 20%
• Feature Reduction Techniques 20%
• Low Detection 20%
• Multi-class Classification 20%