doi: 10.4304/jsw.6.6.1025-1033
Identity Attributes Mining, Metrics Composition and Information Fusion Implementation Using Fuzzy Inference System
- 1 Harbin Institute of Technology, School of Computer Science, Harbin, China
- 2 University 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.
Keywords
- identity attributes
- metrics
- informatio
How to Cite
Jackson Phiri, Tie Jun Zhao, and 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. https://doi.org/ 10.4304/jsw.6.6.1025-1033
Copyright & License
Copyright © 2011 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).