A Deep Belief Networks Intrusion Detection Method Based on Generative Adversarial Networks-Reference-Cited by-同舟云学术

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A Deep Belief Networks Intrusion Detection Method Based on Generative Adversarial Networks

Published:2024-03-29 Issue: Volume: Page:471-476
ISSN:
Container-title:2024 5th International Seminar on Artificial Intelligence, Networking and Information Technology (AINIT)
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Author:

Wei Yi¹,Nong Yingxiong¹,Li Zhe¹,Pan Jian¹,Yang Zhenyu¹,Zheng Zezhang²,Chen Ningjiang³

Affiliation:

1. China Tobacco Guangxi Industrial Co., Ltd,Nanning,China

2. School of Computer, Electronics and Information Guangxi University,Nanning,China

3. School of Computer, Electronics and Information, Guangxi University, (Guangxi University),Guangxi Intelligent Digital Services Research Center of Engineering Technology Key Laboratory of Parallel, Distributed and Intelligent Computing,Nanning,China

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx8/10579949/10579951/10581576.pdf?arnumber=10581576

Reference18 articles.

1. Big Data Based Intelligent Operation and Maintenance Platform

2. Construction Theory for a Building Intelligent Operation and Maintenance System Based on Digital Twins and Machine Learning

3. An Intrusion Detection System Based on Deep Belief Networks

4. Forecasting and Anomaly Detection approaches using LSTM and LSTM Autoencoder techniques with the applications in supply chain management

5. Variational LSTM Enhanced Anomaly Detection for Industrial Big Data

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