Computer Science ›› 2018, Vol. 45 ›› Issue (11): 164-168.doi: 10.11896/j.issn.1002-137X.2018.11.025

• Information Security • Previous Articles     Next Articles

Intrusion Detection Method Based on Intuitionistic Fuzzy Time Series Forecasting Model in Cyberspace

XING Rui-kang, LI Cheng-hai, FAN Xiao-shi   

  1. (College of Air and Missile Defense,Air Force Engineering University,Xi’an 710051,China)
  • Received:2017-11-20 Published:2019-02-25

Abstract: The cyberspace is an emerging combat space that has emerged under the conditions of informatization deve-lopment with the major changes in the world’s military,and has a particularly important impact on air defense and antimissile confrontation.Due to the imperfect security mechanism,the threats that cyberspace faces are constantly increa-sing.Based on this background,this paper proposed an intrusion detection method based on the intuitionistic fuzzy time series forecasting model.This methods calculates the intuitionistic fuzzy prediction error of each characteristic attribute of network data,and distinguishes normal data from intrusion attacks by intuitionistic fuzzy prediction error,so as to achieve the purpose of detection and early warning.Based on this,an intrusion detection framework is established,and a simulation simulation experiment platform is set up to simulate the effectiveness and effectiveness of the algorithm by simulating an abstract and simplified network cyberspace confrontation model.The experimental results show that this method is effective and improves the detection rate of model to some extent.

Key words: Cyberspace, Fuzzy sets, IFTS, Intrusion detection

CLC Number: 

  • TP301.6
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