Journal on Communications ›› 2018, Vol. 39 ›› Issue (8): 29-36.doi: 10.11959/j.issn.1000-436x.2018134

• Artificial Intelligence and Network Security • Previous Articles     Next Articles

Network security threat warning method based on qualitative differential game

Shirui HUANG1,Hengwei ZHANG1,2(),Jindong WANG1,Ruiyu DOU1   

  1. 1 The Third Institute,Information Engineering University,Zhengzhou 450001,China
    2 Science and Technology on Information Assurance Laboratory,Beijing 100093,China
  • Revised:2018-07-17 Online:2018-08-01 Published:2018-09-13
  • Supported by:
    The National Natural Science Foundation of China(61303074);The National Natural Science Foundation of China(61309013);The Science and Technology Research Project of Henan Province(182102210144);The Opening Foundation of Sciense and Technology on Information Assurance Laboratory(KJ-15-110)

Abstract:

Most current network security research based on game theory adopts the static game or multi-stage dynamic game model,which does not accord with the real-time change and continuity of the actual network attack-defense process.To make security threats warning more consistent with the attack-defense process,the threat propagation process was analyzed referring to the epidemic model.Then the network attack-defense game model was constructed based on the qualitative differential game theory,by which the evolution of the network security state could be predicted.Based on the model,the qualitative differential game solution method was designed to construct the attack-defense barrier and divide the capture area.Furthermore,the threat severity in different security states were evaluated by introducing multidimensional Euclidean distance.By designing the warning algorithm,the dynamic warning of the network security threat was realized,which had better accuracy and timeliness.Finally,simulation results verify the effectiveness of the proposed algorithm and model.

Key words: network security threat, network attack and defense, threat warning, qualitative differential game, warning algorithm

CLC Number: 

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