Journal on Communications ›› 2017, Vol. 38 ›› Issue (Z2): 26-29.doi: 10.11959/j.issn.1000-436x.2017272

• Papers • Previous Articles     Next Articles

Keystroke features recognition based on stable linear discriminant analysis

Wei-guo SHEN1,2,Wei WANG1,2   

  1. 1 Science and Technology on Communication Information Security Control Laboratory,Jiaxing 314033,China
    2 No.36 Research Institute of CETC,Jiaxing 314033,China
  • Online:2017-11-01 Published:2018-06-07

Abstract:

A novel keystroke features recognition method based on stable linear discriminant Analysis (SLDA) was put forward.First of all,it maximum the dispersion between different sequences,while minimizing the dispersion between the same sequence set,maintain the best discriminant characteristics of the keystroke sequences.Secondly,the local similarity graph between keystroke sequences is constructed,minimizing the dispersion of the local similarity sequences,to keep the local similarity of keystroke sequences.Finally,based on the principles above,the feature of keystroke sequences are extracted,and the nearest neighbor classification criterion is used to judge the outputs.The effectiveness of the proposed method is certified by experiment results.

Key words: identity authentication, keystroke recognition, feature extraction, stable linear discriminant analysis

CLC Number: 

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