Information Density based Bayes Algorithm for Cloud Platform Intrusion Detection

Authors

Du Ye, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China;
Tiantian Zhang, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China;
Meihong Li, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100044, China;

Abstract

Abstract: For getting better data classification results of cloud platform intrusion detection, and improving the detection accuracy and performance, a Bayes algorithm based on information density was proposed. The complete probability of data characteristics was constructed, and the uncertainty of information was represented by information entropy. The information density was defined to describe the distribution of information uncertainty. The improved algorithm was introduced, and the convergence and time complexity were analyzed. The simulation experiment results show that the method can effectively reduce the data loss and exposethe relationship between data characteristics and data type, which can further classify the detection data of cloud platform accurately with high detection rate and low false positive rate.

Recommended Citation

Ye, Du; Zhang, Tiantian; and Li, Meihong (2019) "Information Density based Bayes Algorithm for Cloud Platform Intrusion Detection," Journal of System Simulation: Vol. 30: Iss. 2, Article 42.
DOI: 10.16182/j.issn1004731x.joss.201802042
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss2/42

First Page

714

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201802042

Last Page

722

CLC

TP309.2

Recommended Citation

Du Ye, Zhang Tiantian, Li Meihong. Information Density based Bayes Algorithm for Cloud Platform Intrusion Detection[J]. Journal of System Simulation, 2018, 30(2): 714-722.

DOI

10.16182/j.issn1004731x.joss.201802042