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A Study on an Efficient and Robust Differential Privacy Scheme Using a Tag Field in Medical Environment

  • Journal of The Korea Society of Computer and Information
  • Abbr : JKSCI
  • 2019, 24(11), pp.109-117
  • DOI : 10.9708/jksci.2019.24.11.109
  • Publisher : The Korean Society Of Computer And Information
  • Research Area : Engineering > Computer Science
  • Received : August 21, 2019
  • Accepted : October 14, 2019
  • Published : November 29, 2019

Kim Soon Seok 1

1한라대학교

Accredited

ABSTRACT

Recently, the invasion of privacy in medical information has been issued following the interest in the secondary use of mass medical information. The mass medical information is very useful information that can be used in various fields such as disease research and prevention. However, due to privacy laws such as the Privacy Act and Medical Law, this information, including patients' or health professionals' personal information, is difficult to utilize as a secondary use of mass information. To do these problem, various methods such as k-anonymity, l-diversity and differential-privacy that can be utilized while protecting privacy have been developed and utilized in this field. In this paper, we discuss the differential privacy processing of the various methods that have been studied so far, and discuss the problems of differential privacy using Laplace noise and the previously proposed differential privacy. Finally, we propose a new scheme to solve the existing problem by adding a 1-bit status field to the last column of a given data set to confirm the response to queries from analysts.

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