doi: 10.4304/jsw.6.6.1025-1033
Identity Attributes Mining, Metrics Composition and Information Fusion Implementation Using Fuzzy Inference System
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
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)
Abbreviated Title: J. Softw.
Frequency: Quarterly
APC: 500USD
DOI: 10.17706/JSW
Editor-in-Chief: Prof. Antanas Verikas
Executive Editor: Ms. Cecilia Xie
Abstracting/ Indexing: DBLP, EBSCO,
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