A Security Situation Prediction Algorithm Based on HMM in Mobile Network

被引：12

作者：

Liang, Wei ^{[1
]}

Long, Jing ^{[2
]}

Chen, Zuo ^{[2
]}

Yan, Xiaolong ^{[2
]}

Li, Yanbiao ^{[3
]}

Zhang, Qingyong ^{[4
]}

Li, Kuan-Ching ^{[5
]}

机构：

[1] Xiamen Univ Technol, Sch Optoelect & Commun Engn, Xiamen 361024, Peoples R China

[2] Hunan Univ, Coll Comp Sci & Elect Engn, Changsha 410082, Hunan, Peoples R China

[3] Univ Calif Los Angeles, Dept Comp Sci, Los Angeles, CA 90024 USA

[4] Fujian Univ Technol, Fujian Key Lab Automot Elect & Elect Drive, Fuzhou 350118, Fujian, Peoples R China

[5] Providence Univ, Dept Comp Sci & Informat Engn, Taichung 43301, Taiwan

来源：

WIRELESS COMMUNICATIONS & MOBILE COMPUTING | 2018年

基金：

美国国家科学基金会;

关键词：

D O I：

10.1155/2018/5380481

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The increasingly severe network security situation brings unanticipated challenges to mobile networking. Traditional HMM (Hidden Markov Model) based algorithms for predicting the network security are not accurate, and to address this issue, a weighted HMM based algorithm is proposed to predict the security situation of the mobile network. The multiscale entropy is used to address the low speed of data training in mobile network, whereas the parameters of HMM situation transition matrix are also optimized. Moreover, the autocorrelation coefficient can reasonably use the association between the characteristics of the historical data to predict future security situation. Experimental analysis on DA RPA2000 shows that the proposed algorithm is highly competitive, with good performance in prediction speed and accuracy when compared to existing design.

引用

页数：11

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