An Asynchronous Federated Learning Arbitration Model for Low-Rate DDoS Attack Detection-Reference-Cited by-同舟云学术

An Asynchronous Federated Learning Arbitration Model for Low-Rate DDoS Attack Detection

Author:

Liu Zengguang¹^ORCID,Guo Cuiyun²,Liu Deyong³,Yin Xiaochun²^ORCID

Affiliation:

1. School of Information Engineering, Shandong Vocational College of Science and Technology, Weifang, China

2. School of Computer Science and Technology, Weifang University of Science and Technology, Shouguang, China

3. Shandong Software Engineering Technology Center, WeiFang University of Science and Technology, Shouguang, China

Funder

Key Technologies Research and Development Program of Weifang

Foundation for the Talents by the Shandong Vocational College of Science and Technology

Foundation for the Talents by the Weifang University of Science and Technology

Natural Science Foundation of Shandong Province

Key Research and Development Program of Shandong Province

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

Reference30 articles.

1. Communication-efficient learning of deep networks from decentralized data;mcmahan;arXiv 1602 05629,2016

2. SynGAN: Towards generating synthetic network attacks using GANs;charlier;arXiv 1908 09899,2019

3. An intrusion detection method based on federated learning and convolutional neural network;wang;Netinfo Security,2020

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