MuDeLA: multi-level deep learning approach for intrusion detection systems
Author:
Affiliation:
1. Kerbala Technical Institute, Al-Furat Al-Awsat Technical University, Kerbala, Iraq
2. Department of Computer Science, University of Babylon, Babylon, Iraq
Publisher
Informa UK Limited
Subject
Computer Graphics and Computer-Aided Design,Computer Science Applications,Hardware and Architecture,Software
Link
https://www.tandfonline.com/doi/pdf/10.1080/1206212X.2023.2275084
Reference53 articles.
1. A Comparative Study of AI-Based Intrusion Detection Techniques in Critical Infrastructures
2. Ensemble Classifiers for Network Intrusion Detection Using a Novel Network Attack Dataset
3. A survey of intrusion detection from the perspective of intrusion datasets and machine learning techniques
4. A survey on intrusion detection and prevention systems in digital substations
5. Using machine learning and statistical models for intrusion detection;Nalavade KC.;Int J Comput Appl,2020
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4. Feature Extraction and Anomaly Detection Using Different Autoencoders for Modeling Intrusion Detection Systems;Arabian Journal for Science and Engineering;2024-04-17
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