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Identity attributes mining, metrics composition and information fusion implementation using fuzzy inference system

  • Jackson Phiri*
  • , Tie Jun Zhao
  • , Jameson Mbale
  • *Corresponding author for this work
  • School of Computer Science and Technology, Harbin Institute of Technology
  • University of Namibia

Research output: Contribution to journalArticlepeer-review

Abstract

Term weight a technique in text mining and entropy from Shannon's information theory are both used to quantify information. In this paper, using term weight and entropy, Sugeno-Style fuzzy inference is envisaged in the implementation of information fusion in a multimode authentication system in an effort to provide a solution to identity theft and fraud. Three corpora are used to mine the identity attributes and generate the statistics required to compose the metrics values from the application forms and questionnaires using term weight and entropy. Triangular and Sigmoidally shaped membership functions are used in the fuzzification of the three inputs categories namely biometrics, pseudo metrics and device based credentials.

Original languageEnglish
Pages (from-to)1025-1033
Number of pages9
JournalJournal of Software
Volume6
Issue number6
DOIs
StatePublished - Jun 2011
Externally publishedYes

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