Building an accretive authentication system using a RBF network

Qiuming Zhu, Luzheng Liu

Research output: Contribution to conferencePaper

Abstract

A computerized authentication system should be able to admit new authentic entries continuously while maintain the existing entry records and an uninterrupted system operation. In this paper, we describe a competitive RBF neural network that is able to incrementally construct itself in response to the pattern samples presented to the system. The neural network is thus a suitable choice for authentication system applications. The accretion property of the neural network is made possible by allowing each pattern class (an authentic entry) being modeled in multiple hyper-ellipsoidal distributions, and mapping these distributions to multiple RBF neural units.

Original languageEnglish (US)
Pages2876-2881
Number of pages6
StatePublished - 1999
EventInternational Joint Conference on Neural Networks (IJCNN'99) - Washington, DC, USA
Duration: Jul 10 1999Jul 16 1999

Other

OtherInternational Joint Conference on Neural Networks (IJCNN'99)
CityWashington, DC, USA
Period7/10/997/16/99

ASJC Scopus subject areas

  • Software
  • Artificial Intelligence

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  • Cite this

    Zhu, Q., & Liu, L. (1999). Building an accretive authentication system using a RBF network. 2876-2881. Paper presented at International Joint Conference on Neural Networks (IJCNN'99), Washington, DC, USA, .