A Hybrid Deep Learning Anomaly Detection Framework for Intrusion Detection

Author:

Kale Rahul1,Lu Zhi1,Fok Kar Wai1,Thing Vrizlynn L. L.1

Affiliation:

1. ST Engineering,Singapore

Publisher

IEEE

Cited by 16 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. A review of digital twins and their application in cybersecurity based on artificial intelligence;Artificial Intelligence Review;2024-07-10

2. Generative Adversarial Networks for Robust Anomaly Detection in Noisy IoT Environments;ICC 2024 - IEEE International Conference on Communications;2024-06-09

3. Multi-agent Reinforcement Learning-based Network Intrusion Detection System;NOMS 2024-2024 IEEE Network Operations and Management Symposium;2024-05-06

4. Robust Anomaly Detection in IoT Networks using Deep SVDD and Contractive Autoencoder;2024 IEEE International Systems Conference (SysCon);2024-04-15

5. A Review of Hybrid Cyber Threats Modelling and Detection Using Artificial Intelligence in IIoT;Computer Modeling in Engineering & Sciences;2024

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