Title:
DE-IDENTIFICATION METHOD FOR BIG DATA
Document Type and Number:
WIPO Patent Application WO/2020/241943
Kind Code:
A1
Abstract:
The present invention relates to a de-identification method for big data, for anonymizing the big data so that the big data may be freely distributed to an external system without concern about personal information leakage and enabling a statistical value calculated from the distributed data to be maximally close to a statistical value of original data to thereby secure the reliability of statistical analysis. According to the present invention, records in which values of abstraction reference fields are all the same and the number thereof is less than or equal to N are separately grouped without being excluded from being abstracted, and a connection-type attribute value including an occurrence rate value of a corresponding category attribute value in a group is allocated as an attribute value of an abstracted record to minimize abstraction missing data, so that the statistical value calculated from the distributed data becomes maximally close to the statistical value of the original data, thereby securing the reliability of the statistical analysis.
Inventors:
LEE WON SUK (KR)
Application Number:
PCT/KR2019/006586
Publication Date:
December 03, 2020
Filing Date:
May 31, 2019
Export Citation:
Assignee:
BOALA CO LTD (KR)
International Classes:
G06F21/62; G06F16/22; G06F17/18
Foreign References:
| KR101784265B1 | 2017-10-12 | |||
| KR20170078983A | 2017-07-10 | |||
| KR20180060390A | 2018-06-07 | |||
| US20150235049A1 | 2015-08-20 | |||
| US20120131481A1 | 2012-05-24 | |||
| US20150324607A1 | 2015-11-12 |
Attorney, Agent or Firm:
WELL PATENT LAW FIRM (KR)
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