De-identification and Privacy Issues on Bigdata Transformation

  • Lee, Allen Hyojun
  • Cho, Steve Siheon
  • Seong, Jessica Jiwon
  • Lee, Suan
  • Lee, Wookey
Citations

WEB OF SCIENCE

6
Citations

SCOPUS

13

초록

As the number of data in various industries and government sectors is growing exponentially, the '7V' concept of big data aims to create a new value by indiscriminately collecting and analyzing information from various fields. At the same time as the ecosystem of the ICT industry arrives, big data utilization is treatened by the privacy attacks such as infringement due to the large amount of data. To manage and sustain the controllable privacy level, there need some recommended dc-identification techniques. This paper exploits those de-identification processes and three types of commonly used privacy models. Furthermore, this paper presents use cases which can he adopted those kinds of technologies and future development directions.

키워드

Big DataPrivacypersonal-informationk-anonymityl-diversityt-closeness
제목
De-identification and Privacy Issues on Bigdata Transformation
저자
Lee, Allen HyojunCho, Steve SiheonSeong, Jessica JiwonLee, SuanLee, Wookey
DOI
10.1109/BigComp48618.2020.00-14
발행일
2020
유형
Proceedings Paper
저널명
2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (BIGCOMP 2020)
페이지
514 ~ 519