Conditional Variational Autoencoder for Prediction and Feature Recovery Applied to Intrusion Detection in IoT

Author:

Lopez-Martin Manuel,Carro Belen,Sanchez-Esguevillas Antonio,Lloret JaimeORCID

Publisher

MDPI AG

Subject

Electrical and Electronic Engineering,Biochemistry,Instrumentation,Atomic and Molecular Physics, and Optics,Analytical Chemistry

Cited by 204 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. Exploring the influence of the choice of prior of the Variational Auto-Encoder on cybersecurity anomaly detection;Proceedings of the 19th International Conference on Availability, Reliability and Security;2024-07-30

2. Applying Generative Machine Learning to Intrusion Detection: A Systematic Mapping Study and Review;ACM Computing Surveys;2024-06-22

3. The Method of Restoring Lost Information from Sensors Based on Auto-Associative Neural Networks;Applied System Innovation;2024-06-20

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

5. Intrusion Detection System Using Hybrid Model of Denoising Autoencoder and Ladder Variational Autoencoder;2024 10th International Conference on Communication and Signal Processing (ICCSP);2024-04-12

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