A network security situation prediction method based on hidden Markov model

Xiong ZHAN; Hao GUO; Peng ZHANG; Shu MAO

doi:10.11959/j.issn.1000-0801.2015394

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A network security situation prediction method based on hidden Markov model

Network and information security | 更新时间：2024-06-05

- A network security situation prediction method based on hidden Markov model
- Telecommunications Science Vol. 31, Issue Z1, Pages: 79-84(2015)
- 作者机构：
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.1000-0801.2015394
  CLC： TP393.08
- Published Online：20 December 2015，
  
  Published：20 December 2015
- 稿件说明：
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Xiong ZHAN, Hao GUO, Peng ZHANG, et al. A network security situation prediction method based on hidden Markov model[J]. Telecommunications science, 2015, 31(Z1): 79-84.
DOI：

Xiong ZHAN, Hao GUO, Peng ZHANG, et al. A network security situation prediction method based on hidden Markov model[J]. Telecommunications science, 2015, 31(Z1): 79-84. DOI： 10.11959/j.issn.1000-0801.2015394.

摘要

摘要：针对网络安全态势预测动态、实时等特性，设计了基于隐马尔可夫模型网络安全态势预测模型。根据t时刻的网络安全态势计算出t+1时刻的态势，同时结合最大熵算法，对态势进行一致性判定，提高了预测准确率。分析及模拟实验表明该基于隐马尔可夫模型的网络安全态势预测方法具有自主学习及主动防御特征，同时平衡了速度和准确度要求，能够高效、准确地进行网络安全态势预测。

Abstract

Aiming at the dynamic and real-time characteristics of network security situation prediction

a network security situation prediction model based on hidden Markov model（HMM）was designed.According to the HMM

the situation in t+1 from t time can be calculated.Meanwhile

the maximum entropy algorithm was combinated with HMM to improve the accuracy rate.The analysis and simulation experiments show that the method has the characteristics of autonomous learning and active defense

and it also balance the speed and accuracy.

关键词

Keywords

references

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