<abstract xmlns="http://www.w3.org/1999/xhtml"><p> In health care databases, there are tireless and antagonistic interests between data mining research and privacy preservation, the more you try to hide sensitive private information, the less valuable it is for analysis. In this paper, we give an outlook on data anonymization problems by case studies. We give a summary on the state-of-the-art health care data anonymization issues including legal environment and expectations, the most common attacking strategies on privacy, and the proposed metrics for evaluating usefulness and privacy preservation for anonymization. Finally, we summarize the strength and the shortcomings of different approaches and techniques from the literature based on these evaluations.</p></abstract>

In health care databases, there are tireless and antagonistic interests between data mining research and privacy preservation, the more you try to hide sensitive private information, the less valuable it is for analysis. In this paper, we give an outlook on data anonymization problems by case studies. We give a summary on the state-of-the-art health care data anonymization issues including legal environment and expectations, the most common attacking strategies on privacy, and the proposed metrics for evaluating usefulness and privacy preservation for anonymization. Finally, we summarize the strength and the shortcomings of different approaches and techniques from the literature based on these evaluations.

Survey on privacy preserving data mining techniques in health care databases

U1 Research 2 INFOPARK Gábor Dénes Budapest, Hungary

Acta Universitatis Sapientiae, Informatica

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

{"article-title":"Survey on privacy preserving data mining techniques in health care databases"}

In health care databases, there are tireless and antagonistic interests between data mining research and privacy preservation, the more you try to hide...

Survey on privacy preserving data mining techniques in health care databases

Published Online: Jun 27, 2014

Page range: 33 - 55

Received: Oct 09, 2013

DOI: https://doi.org/10.2478/ausi-2014-0017

Keywords
anonymization, privacy preservation, health care database, survey, data mining, sensitive data

© 2014

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Survey on privacy preserving data mining techniques in health care databases

Published Online: Jun 27, 2014

Page range: 33 - 55

Received: Oct 09, 2013

DOI: https://doi.org/10.2478/ausi-2014-0017

Keywordsanonymization, privacy preservation, health care database, survey, data mining, sensitive data

© 2014

This article is distributed under the terms of the Creative Commons Attribution Non-Commercial License, which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

Keywords
anonymization, privacy preservation, health care database, survey, data mining, sensitive data