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This paper investigates the performance of different feature selection techniques such as ranking and subset-based techniques, aiming to find the optimum collection of features to detect attacks with an appropriate… Click to show full abstract
This paper investigates the performance of different feature selection techniques such as ranking and subset-based techniques, aiming to find the optimum collection of features to detect attacks with an appropriate classifier. The results reveal that more accuracy of detection and less false alarms are obtained after eliminating the redundant features and determining the most useful set of features, which increases the intrusion detection system (IDS) performance.
Keywords:
subset based;
detection;
feature selection;
based techniques;
ranking subset;
intrusion detection
Journal Title: Wireless Personal Communications
Year Published: 2020
Link to full text (if available)
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Journal Title: Wireless Personal Communications
Year Published: 2020
Link to full text (if available)
Share on Social Media: Sign Up to like & get
recommendations!