DDoS Detection and Protection Based on Cloud Computing Platform. (August 2020)

• Record Type: Journal Article
• Authors: Jili, Tianwen; Xiao, Nanfeng
• Is Part Of: Journal of physics. Volume 1621(2020)
• Publication Date: 2020-08
• Subjects: Cloud computing -- software-defined network (SDN) -- distributed denial service attack -- attack detection; Physics -- Congresses; 530.5
• DOI: 10.1088/1742-6596/1621/1/012005
• Languages: English
• ISSNs: 1742-6588

Abstract

Abstract: Currently, the distributed denial service attacks (DDoS) are increased rampantly on the internet, the threshold of such attacks is relatively low for the malicious attackers. Therefore, the DDoS attacks are serious threats to the security availability of the cloud computing. Aiming at the threats, this paper studies the malicious traffic identification and the detection scheme of the denial service attack under the soft-ware-defined Network (SDN), which uses the SDN forwarder to distinguish the DDoS attack traffic and adopt the corresponding filtering means to achieve protection for the distributed denial service attack. This paper firstly implements cloud platform resource calls, then an attack detection technology based on information entropy is proposed and implemented to carry out the DDoS attack detection, because the size of the entropy value can show the discrete or aggregated characteristics of the current data set, which can be used to detect abnormal data traffic. At last, the experiments are also carried out to verify and analyze the effectiveness of the DDoS attack detection and the protection methods.