X-CBA: Explainability Aided CatBoosted Anomal-E for Intrusion Detection System-Reference-Cited by-同舟云学术

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X-CBA: Explainability Aided CatBoosted Anomal-E for Intrusion Detection System

Published:2024-06-09 Issue: Volume:33 Page:2288-2293
ISSN:
Container-title:ICC 2024 - IEEE International Conference on Communications
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Author:

Kaya Kiymet¹,Ak Elif¹,Bas Sumeyye¹,Canberk Berk²,Oguducu Sule Gunduz³

Affiliation:

1. Istanbul Technical University,Department of Computer Engineering,Istanbul,Turkey

2. School of Computing, Engineering and Built Environment, Edinburgh Napier University,Edinburgh

3. Istanbul Technical University,Department of Artificial Intelligence and Data Engineering,Istanbul,Turkey

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10622104/10622158/10622177.pdf?arnumber=10622177

Reference27 articles.

1. Explainable Intrusion Detection Systems (X-IDS): A Survey of Current Methods, Challenges, and Opportunities

2. Adversarial Machine Learning for Network Intrusion Detection Systems: A Comprehensive Survey

3. FSC: Two-Scale AI-Driven Fair Sensitivity Control for 802.11ax Networks

4. Graph Neural Networks for Intrusion Detection: A Survey

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