@inproceedings{740147dabb5c4743a0eafd68046f3ca0,
title = "A new approach to preserve privacy data mining based on fuzzy theory in numerical database",
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.",
keywords = "Privacy protection, anonymity, data mining, database utility, fuzzy theory",
author = "Run Cui and Kim, {Hyoung Joong}",
year = "2014",
doi = "10.1117/12.2051002",
language = "English",
isbn = "9781628410013",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
booktitle = "Fifth International Conference on Graphic and Image Processing, ICGIP 2013",
note = "5th International Conference on Graphic and Image Processing, ICGIP 2013 ; Conference date: 26-10-2013 Through 27-10-2013",
}