Network Security Situation Assessment Model Based on Extended Hidden Markov

A network security situation assessment system based on the extended hidden Markov model is designed in this paper. Firstly, the standard hidden Markov model is expanded from five-tuple to seven-tuple, and two parameters of network defense efficiency and risk loss vector are added so that the model...

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Main Authors: Yiwei Liao, Guosheng Zhao, Jian Wang, Shu Li
Format: Article
Language:English
Published: Hindawi Limited 2020-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2020/1428056
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spelling doaj-910c620e04904102a5531e59ac3ca2292020-11-25T03:11:35ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472020-01-01202010.1155/2020/14280561428056Network Security Situation Assessment Model Based on Extended Hidden MarkovYiwei Liao0Guosheng Zhao1Jian Wang2Shu Li3College of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, ChinaCollege of Computer Science and Information Engineering, Harbin Normal University, Harbin 150025, ChinaSchool of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150001, ChinaSchool of Computer Science and Technology, Harbin University of Science and Technology, Harbin 150001, ChinaA network security situation assessment system based on the extended hidden Markov model is designed in this paper. Firstly, the standard hidden Markov model is expanded from five-tuple to seven-tuple, and two parameters of network defense efficiency and risk loss vector are added so that the model can describe network security situation more completely. Then, an initial algorithm of state transition matrix was defined, observation vectors were extracted from the fusion of various system security detection data, the network state transition matrix was created and modified by the observation vectors, and a solution procedure of the hidden state probability distribution sequence based on extended hidden Markov model was derived. Finally, a method of calculating risk loss vector according to the international definition was designed and the current network risk value was calculated by the hidden state probability distribution; then the global security situation was assessed. The experiment showed that the model satisfied practical applications and the assessment result is accurate and effective.http://dx.doi.org/10.1155/2020/1428056
collection DOAJ
language English
format Article
sources DOAJ
author Yiwei Liao
Guosheng Zhao
Jian Wang
Shu Li
spellingShingle Yiwei Liao
Guosheng Zhao
Jian Wang
Shu Li
Network Security Situation Assessment Model Based on Extended Hidden Markov
Mathematical Problems in Engineering
author_facet Yiwei Liao
Guosheng Zhao
Jian Wang
Shu Li
author_sort Yiwei Liao
title Network Security Situation Assessment Model Based on Extended Hidden Markov
title_short Network Security Situation Assessment Model Based on Extended Hidden Markov
title_full Network Security Situation Assessment Model Based on Extended Hidden Markov
title_fullStr Network Security Situation Assessment Model Based on Extended Hidden Markov
title_full_unstemmed Network Security Situation Assessment Model Based on Extended Hidden Markov
title_sort network security situation assessment model based on extended hidden markov
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2020-01-01
description A network security situation assessment system based on the extended hidden Markov model is designed in this paper. Firstly, the standard hidden Markov model is expanded from five-tuple to seven-tuple, and two parameters of network defense efficiency and risk loss vector are added so that the model can describe network security situation more completely. Then, an initial algorithm of state transition matrix was defined, observation vectors were extracted from the fusion of various system security detection data, the network state transition matrix was created and modified by the observation vectors, and a solution procedure of the hidden state probability distribution sequence based on extended hidden Markov model was derived. Finally, a method of calculating risk loss vector according to the international definition was designed and the current network risk value was calculated by the hidden state probability distribution; then the global security situation was assessed. The experiment showed that the model satisfied practical applications and the assessment result is accurate and effective.
url http://dx.doi.org/10.1155/2020/1428056
work_keys_str_mv AT yiweiliao networksecuritysituationassessmentmodelbasedonextendedhiddenmarkov
AT guoshengzhao networksecuritysituationassessmentmodelbasedonextendedhiddenmarkov
AT jianwang networksecuritysituationassessmentmodelbasedonextendedhiddenmarkov
AT shuli networksecuritysituationassessmentmodelbasedonextendedhiddenmarkov
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