Work

Using SVM to Detect DDoS Attack in SDN Network

Year: 2018

Type: conference-paper

Abstract: Software Defined Network(SDN) controller has the global view of the network, but it is vulnerable to DDoS attack. This paper proposes a new model to detect DDoS attack in SDN based on SVM . Firstly The model extracts several key features from the packet-in messages and measures the distribution of each feature by using entropy, then uses trained Support Vector Machine(SVM) algorithm to detect the DDoS attack. Experiments shows that this method can detect security events with high efficiency and mitigate the DDoS attack in real-time.

Source: IOP Conference Series Materials Science and Engineering

DOI: 10.1088/1757-899x/466/1/012003

Authors: Dong Li, Chang Yu, Qizhao Zhou, Junqing Yu

Institution: Huazhong University of Science and Technology

Language: English

Topic: Network Security and Intrusion Detection

Subfield: Computer Networks and Communications

Field: Computer Science

Domain: Physical Sciences

Open Access status: diamond

OpenAlex ID: W2906883204

FWCI: 2.031

Cites: 10

Cited by: 45

Related to: 10