An Explainable AI-Based Intrusion Detection System for DNS Over HTTPS (DoH) Attacks-Reference-Cited by-同舟云学术

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An Explainable AI-Based Intrusion Detection System for DNS Over HTTPS (DoH) Attacks

Published:2022 Issue: Volume:17 Page:2339-2349
ISSN:1556-6013
Container-title:IEEE Transactions on Information Forensics and Security
language:
Short-container-title:IEEE Trans.Inform.Forensic Secur.

Author:

Zebin Tahmina¹^ORCID,Rezvy Shahadate²,Luo Yuan³^ORCID

Affiliation:

1. School of Computing Science, University of East Anglia, Norwich, U.K

2. Department of Computer Science, School of Science, Technology and Health, York St John University, York, U.K

3. Faculty of Science and Technology, Middlesex University London, London, U.K

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Safety, Risk, Reliability and Quality

Link

http://xplorestaging.ieee.org/ielx7/10206/9652463/09796558.pdf?arnumber=9796558

Reference24 articles.

1. Detecting Malicious DNS over HTTPS Traffic in Domain Name System using Machine Learning Classifiers

2. Network Attack Detection with QNNBADT in Minimal Response Times Using Minimized Features

3. Analysis and investigation of malicious DNS queries using CIRA-CIC-DoHBrw-2020 dataset;jafar;Manchester J Artif Intell Appl Sci,2021

4. A unified approach to interpreting model predictions;lundberg;Proc 31st Int Conf Neural Inf Process Syst,2017

5. Detection of DoH Tunnels using Time-series Classification of Encrypted Traffic

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