Supervised Feature Selection Techniques in Network Intrusion Detection: a Critical Review

11 April 2021

Papers citing "Supervised Feature Selection Techniques in Network Intrusion Detection: a Critical Review"

6 / 6 papers shown

Title
Pruning-Based TinyML Optimization of Machine Learning Models for Anomaly Detection in Electric Vehicle Charging Infrastructure Fatemeh Dehrouyeh I. Shaer Soodeh Nikan F. Badrkhani Ajaei Abdallah Shami 68 0 0 19 Mar 2025
Exploring Feature Importance and Explainability Towards Enhanced ML-Based DoS Detection in AI Systems Paul Badu Yakubu Evans Owusu Lesther Santana Mohamed Rahouti Abdellah Chehri Kaiqi Xiong AAML 21 0 0 04 Nov 2024
INTELLECT: Adapting Cyber Threat Detection to Heterogeneous Computing Environments Simone Magnani Liubov Nedoshivina Roberto Doriguzzi-Corin Stefano Braghin Domenico Siracusa 61 0 0 17 Jul 2024
Deep Neural Networks based Meta-Learning for Network Intrusion Detection A. Sohail B. Ayisha I. Hameed Muhammad Mohsin Zafar Hani Alquhayz Asifullah Khan 34 5 0 18 Feb 2023
A Tent Lévy Flying Sparrow Search Algorithm for Feature Selection: A COVID-19 Case Study Qin Yang Yuelin Gao Y. Song 19 0 0 20 Sep 2022
Online Feature Selection for Efficient Learning in Networked Systems Xiaoxuan Wang Rolf Stadler 21 0 0 15 Dec 2021