Volume 6 Number 6 (Jun. 2011)
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JSW 2011 Vol.6(6): 1025-1033 ISSN: 1796-217X
doi: 10.4304/jsw.6.6.1025-1033

Identity Attributes Mining, Metrics Composition and Information Fusion Implementation Using Fuzzy Inference System

Jackson Phiri1, Tie Jun Zhao1, Jameson Mbale2

1Harbin Institute of Technology, School of Computer Science, Harbin, China
2University of Namibia, Department of Computer Science, Windhoek, Namibia


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.

Index Terms—identity attributes, metrics, information fusion, fuzzy logic, authentication, term weight, entropy

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Cite: Jackson Phiri, Tie Jun Zhao, Jameson Mbale, "Identity Attributes Mining, Metrics Composition and Information Fusion Implementation Using Fuzzy Inference System," Journal of Software vol. 6, no. 6, pp. 1025-1033, 2011.

General Information

ISSN: 1796-217X (Online)
Frequency:  Quarterly
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Yoyo Y. Zhou
Abstracting/ Indexing: DBLP, EBSCO, CNKIGoogle Scholar, ProQuest, INSPEC(IET), ULRICH's Periodicals Directory, WorldCat, etc
E-mail: jsweditorialoffice@gmail.com
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