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  • 标题:Performance Evaluation of Password Authentication using Associative Neural Memory Models
  • 本地全文:下载
  • 作者:P.E.S.N. Krishna Prasasd ; A.S.N. Chakravarthy ; B.D.C.N. Prasad
  • 期刊名称:International Journal of Advanced Information Technology
  • 印刷版ISSN:2231-1920
  • 电子版ISSN:2231-1548
  • 出版年度:2012
  • 卷号:2
  • 期号:1
  • 出版社:Academy & Industry Research Collaboration Center (AIRCC)
  • 摘要:They are many ways of providing security to user resources. Password authentication is a very important system security procedure to secure user resources. In order to solve the problems with traditional password authentication several methods have been introduced to provide password authentication using Associative Memories like Back Propagation Neural Network (BPNN),Hopfield Neural Network(HP NN),Bidirectional Associative Memories(BAM),Brain-State-in-a Box(BSB). Later Password authentication has been provided using Context-Sensitive Associative Memory Method (CSAM). Here in this paper we proposed performance analysis of password authentication schemes using Associative memories and CSAM using graphical Images. We observe that in comparison to existing layered and associative neural network techniques for graphical images as password, the CSAM method provides better accuracy and quicker response time to registration and password changes
  • 关键词:Authentication; Cryptography; Password
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