Bottom-Up Generalization: A Data Mining Solution to Privacy Protection
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
www.ijsr.net | Open Access | Fully Refereed | Peer Reviewed International Journal

ISSN: 2319-7064

Views: 146 , Downloads: 109 | CTR: 75 % | Weekly Popularity: ⮙1

M.Tech / M.E / PhD Thesis | Computer Science & Engineering | India | Volume 4 Issue 1, January 2015

Bottom-Up Generalization: A Data Mining Solution to Privacy Protection

Vishakha B. Dalvi, Ranjit R. Keole

In recent years, privacy-preserving data mining has been studied extensively, because of the wide proliferation of sensitive information on the internet. This paper investigates data mining as a technique for masking data, therefore, termed data mining based privacy protection. This approach incorporates partially the requirement of a targeted data mining task into the process of masking data so that essential structure is preserved in the masked data. The following privacy problem is considered in this paper a data holder wants to release a version of data for building classification models, but wants to protect against linking the released data to an external source for inferring sensitive information. An iterative bottom-up generalization is adapted from data mining to generalize the data. The generalized data remains useful to classification but becomes difficult to link to other sources. The generalization space is specified by a hierarchical structure of generalizations. A key is identifying the best generalization to climb up the hierarchy at each iteration.

Keywords: Generalization, k-anonymity, privacy-preserving data mining, randomization, re-identification

Edition: Volume 4 Issue 1, January 2015

Pages: 2068 - 2071

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Vishakha B. Dalvi, Ranjit R. Keole, "Bottom-Up Generalization: A Data Mining Solution to Privacy Protection", International Journal of Science and Research (IJSR), https://www.ijsr.net/search_index_results_paperid.php?id=SUB15769, Volume 4 Issue 1, January 2015, 2068 - 2071

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