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SYN Flood Attack Detection in Cloud Computing using Support Vector Machine

期刊名字: TEM JOURNAL - Technology, Education, Management, Informatics (Vol.6, No. 4)

Publication Date:

论文作者 : ;

起始页码 : 752-759

关键字 : Cloud computing; SYN flood; DoS attack; Support Vector Machine;

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论文摘要

Cloud computing is a trending technology, as it reduces the cost of running a business. However, many companies are skeptic moving about towards cloud due to the security concerns. Based on the Cloud Security Alliance report, Denial of Service (DoS) attacks are among top 12 attacks in the cloud computing. Therefore, it is important to develop a mechanism for detection and prevention of these attacks. The aim of this paper is to evaluate Support Vector Machine (SVM) algorithm in creating the model for classification of DoS attacks and normal network behaviors. The study was performed in several phases: a) attack simulation, b) data collection, c)feature selection, and d) classification. The proposedmodel achieved 100% classification accuracy with true positive rate (TPR) of 100%. SVM showed outstanding performance in DoS attack detection and proves that it serves as a valuable asset in the network security area.

更新日期: 2017-12-07 07:18:30