Computer Science ›› 2020, Vol. 47 ›› Issue (7): 287-291.doi: 10.11896/jsjkx.190300045

• Information Security • Previous Articles     Next Articles

Network Security Situation Assessment Method Based on Improved Hidden Markov Model

LI Xin, DUAN Yong-cheng   

  1. College of Information Technology and Network Security,People’s Public Security University of China,Beijing 100038,China
  • Received:2019-03-13 Online:2020-07-15 Published:2020-07-16
  • About author:LI Xin,born in 1977,Ph.D,associate professor.His main research interests include cyber security and so on.
    DUAN Yong-cheng,born in 1995,master.His main research interests include situational awareness and so on.
  • Supported by:
    This work was supported by the National Key R&D Program of China(2017YFC0803700)

Abstract: Cyber security situation awareness,as an effective supplement in cyber security protection measures,is one of the research focus in recent years.In particular,network security situation assessment has become an important research topic in the field of network security.Hidden Markov Model (HMM) can be used in network security situation assessment,which can evalua-te network status in real time,but there are problems such as difficult to configure model parameters and low evaluation accuracy.Therefore,this paper proposes a situation assessment method for improving the Hidden Markov Model,combining the Baum-Welch (BW) parameter optimization algorithm with the Seeker Optimization Algorithm (SOA).Taking advantage of the strong random search ability of SOA,the traditional parameter optimization algorithm is easy to fall into local optimal solution.The optimized parameters are substituted into the HMM,and the network security situation value is obtained through quantitative analysis.Based on the DARPA2000 dataset,this paper uses MATLAB software to verify the proposed method.The experimental results show that compared with BW algorithm,this method can improve the accuracy of the model,and it makes the quantification of the network security situation more reasonable.

Key words: Situation assessment, HMM, SOA, Parameter optimization, Situational awareness

CLC Number: 

  • TP393
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