Privacy preservation in data intensive environment
Healthcare data frameworks have enormously expanded accessibility of medicinal reports and profited human services administration and research work. In many cases, there are developing worries about protection in sharing restorative files. Protection procedures for unstructured restorative conte...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
University of Algarve, ESGHT/CINTURS
2018-04-01
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| Series: | Tourism & Management Studies |
| Subjects: | |
| Online Access: | https://tmstudies.net/index.php/ectms/article/view/1077/pdf_101 |
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| Summary: | Healthcare data frameworks have enormously expanded accessibility of
medicinal reports and profited human services administration and
research work. In many cases, there are developing worries about
protection in sharing restorative files. Protection procedures for
unstructured restorative content spotlight on recognition and expulsion
of patient identifiers from the content, which might be lacking for
safeguarding privacy and information utility. For medicinal services,
maybe related exploration thinks about the therapeutic records of
patients ought to be recovered from various destinations with various
regulations on the divulgence of healthcare data. Considering delicate
social insurance data, privacy protection is a significant concern, when
patients' mediclinical services information is utilized for exploration
purposes. In this article we have used feature selection for getting the
best feature set to be selected for privacy preservation by using PCA
(Principle Component Analysis). After that we have used two methods
K-anonymity and fuzzy system for providing the privacy on medical
databases in data intensive enviroments. The results affirm that the
proposed method has better performance than those of the related
works with respect to factors such as highly sensitive data preservation
with k-anonymity. |
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| ISSN: | 2182-8466 |