XMODOS: An Explainable Model for Denial of Service Attack Detection
Author:
Affiliation:
1. Canadian Institute for Cybersecurity, University of New Brunswick
2. Software Engineering, Concordia University,Department of Computer Science
3. School of Energy, Geoscience, Infrastructure, and Society, Hariot-Watt University,Edinburgh
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10391856/10393862/10394464.pdf?arnumber=10394464
Reference27 articles.
1. Denial of service attack detection and mitigation for internet of things using looking-back-enabled machine learning techniques
2. DDoS attack detection using MLP and Random Forest Algorithms
3. Refined LSTM Based Intrusion Detection for Denial-of-Service Attack in Internet of Things
4. Trust in ai: Interpretability is not necessary or sufficient, while black-box interaction is necessary and sufficient;Shen,2022
5. Explaining the black-box model: A survey of local interpretation methods for deep neural networks
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