SDN traffic anomaly detection method based on convolutional autoencoder and federated learning

Author:

Wang ZiXuan1,Wang Pan1,Sun ZhiXin1

Affiliation:

1. School of Modern Posts, NJUPT,Nanjing,China

Funder

National Key Research and Development Project of China

Publisher

IEEE

Reference15 articles.

1. A survey on federated learning

2. Unsupervised learning approach for network intrusion detection system using autoencoders

3. Enhanced recursive feature elimination

4. Communication-efficient learning of deep networks from decentralized data;mcmahan;Artificial Intelligence and Statistics,2017

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3. TIBS: A Deep-Learning Model for Network Intrusion Detection for SDN Environments;2024 9th International Conference on Computer and Communication Systems (ICCCS);2024-04-19

4. CAFNet: Compressed Autoencoder-based Federated Network for Anomaly Detection;MILCOM 2023 - 2023 IEEE Military Communications Conference (MILCOM);2023-10-30

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