A Comparative Study of Privacy Protection Algorithms Applied to Databases in the Health Area

• Francimaria Nascimento Federal University of Rio Grande do Norte
• Karliane Vale Federal University of Rio Grande do Norte
• Flavius Gorgônio Federal University of Rio Grande do Norte

DOI: https://doi.org/10.5753/sbbd.2018.22247

Abstract

The growing increase in the volume of data which is collected, stored and shared by health institutions creates benefits for the process of decision making based on the knowledge obtained from applying data analysis and data mining techniques, aiming to achieve relevant information. Despite the obtained benefits, sharing this specific kind of data in its original raw format may compromise patients’ privacy. In an attempt to validate solutions for this problem, this article considers and compares data anonymization and perturbation techniques, assessing their efficiency in providing privacy and safety of shared data, more specifically, when applied to databases of the health field.

Keywords: Privacy Protection, Health, Protection Algorithms, Data Disruption, Privacy, Security

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