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On a Coexisting Scheme for Multiple Flows in Multi-radio Multi-channel Wireless Mesh Networks Read chapter Read first chapter

2020 | OriginalPaper | Chapter

Research on DDoS Abnormal Traffic Detection Under SDN Network

Authors : Zhaohui Ma, Jialiang Huang

Published in: Parallel Architectures, Algorithms and Programming

Publisher: Springer Singapore

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Abstract

The seperation of control layer from data layer through SDN (software defined network) enables network administrators to plan the network programmatically without changing network devices, realizing flexible configuration of network devices and fast forwarding of data flows. However, due to its construction, SDN is vulnerable to be attacked by Distributed Denial of Service (DDoS) attack. So it is important to detect DDoS attack in SDN network. This paper presents a DDoS detection scheme based on the machine learning method of SVM (support vector machine) support vector machine in SDN environment. By extracting the flow table information features in SDN network, the data is detected and the data model of DDoS traffic can be trained, and the purpose of DDoS abnormal traffic identification is finally realized.

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Metadata
Title
Research on DDoS Abnormal Traffic Detection Under SDN Network
Authors
Zhaohui Ma
Jialiang Huang
Copyright Year
2020
Publisher
Springer Singapore
Book
Parallel Architectures, Algorithms and Programming

Print ISBN: 978-981-15-2766-1

Electronic ISBN: 978-981-15-2767-8

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-981-15-2767-8_33