Earticle

초록

영어

In recent years, cloud computing is becoming popular in the field of information, however, the development of cloud computing have to face the problem of cloud security. Intrusion Deletion System (IDS) is one of the possible solutions to the problem of cloud security, but the correct rate of general application of the IDS is not very satisfactory, for this purpose we propose a density-based binary Support Vector Machine (SVM) method (D-BSVM). Its main idea is based on the density of each class in the data set, and gets a binary sequence of training, according to this sequence obtained binary SVM training model to predict the behavior of the system. Further, the method for calculating the density is the paralleled, thereby improving efficiency of overall system. Finally, we present experimental results, and by contrast our approach can improve the accuracy and detection rate of IDS.

목차

Abstract
 1. Introduction
 2. Related Works
  2.1. Multi-class SVM
  2.2. Hadoop and MapReduce
 3. The Binary Tree SVM Algorithm based on Density (D-BTSVM)
 4. Experiments
 5. Conclusions and Future Work
 Acknowledgements
 References

키워드

저자

• Mingyuan Yu [ College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China ]
• Shuhang Huang [ College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China ]
• Qing Yu [ College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China ]
• Yan Wang [ College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China ]
• Jiaquan Gao [ College of Computer Science and Technology, Zhejiang University of Technology, Hangzhou 310023, China ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  International Journal of Security and Its Applications

• 간기

  격월간

• pISSN

  1738-9976

• 수록기간

  2008~2016

• 등재여부

  SCOPUS

• 십진분류

  KDC 505 DDC 605