A new approach to preserve privacy data mining based on fuzzy theory in numerical database

Run Cui; Hyoung Joong Kim

doi:10.1117/12.2051002

10 January 2014 A new approach to preserve privacy data mining based on fuzzy theory in numerical database

Run Cui, Hyoung Joong Kim

Proceedings Volume 9069, Fifth International Conference on Graphic and Image Processing (ICGIP 2013); 90691A (2014) https://doi.org/10.1117/12.2051002
Event: Fifth International Conference on Graphic and Image Processing, 2013, Hong Kong, China

Abstract

With the rapid development of information techniques, data mining approaches have become one of the most important tools to discover the in-deep associations of tuples in large-scale database. Hence how to protect the private information is quite a huge challenge, especially during the data mining procedure. In this paper, a new method is proposed for privacy protection which is based on fuzzy theory. The traditional fuzzy approach in this area will apply fuzzification to the data without considering its readability. A new style of obscured data expression is introduced to provide more details of the subsets without reducing the readability. Also we adopt a balance approach between the privacy level and utility when to achieve the suitable subgroups. An experiment is provided to show that this approach is suitable for the classification without a lower accuracy. In the future, this approach can be adapted to the data stream as the low computation complexity of the fuzzy function with a suitable modification.

Citation Download Citation

Run Cui and Hyoung Joong Kim "A new approach to preserve privacy data mining based on fuzzy theory in numerical database", Proc. SPIE 9069, Fifth International Conference on Graphic and Image Processing (ICGIP 2013), 90691A (10 January 2014); https://doi.org/10.1117/12.2051002

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