Central Tendency Feature Selection (CTFS): a novel approach for efficient and effective feature selection in intrusion detection systems

Central Tendency Feature Selection (CTFS): a novel approach for efficient and effective feature selection in intrusion detection systems

In the digital era, the escalation of data generation and cyber threats has heightened the importance of network security. Machine Learning-based Intrusion Detection Systems (IDS) play a crucial role in combating these threats, yet there is a significant gap in their feature selection methodologies....

Full description

Saved in:
Bibliographic Details
Main Authors: Bouke, Mohamed Aly, Abdullah, Azizol, Udzir, Nur Izura, Samian, Normalia
Format: Article
Language:en
Published: Springer 2025
Subjects:
Software
Media Technology
Online Access:http://psasir.upm.edu.my/id/eprint/122296/1/122296.pdf
http://psasir.upm.edu.my/id/eprint/122296/
https://link.springer.com/article/10.1007/s11042-025-20837-8?error=cookies_not_supported&code=6ff301d8-44b9-4ae7-85b8-8989d752fdbe
Tags: Add Tag
No Tags, Be the first to tag this record!

Internet

http://psasir.upm.edu.my/id/eprint/122296/1/122296.pdf
http://psasir.upm.edu.my/id/eprint/122296/
https://link.springer.com/article/10.1007/s11042-025-20837-8?error=cookies_not_supported&code=6ff301d8-44b9-4ae7-85b8-8989d752fdbe

Similar Items