원문정보
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
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
