Paper Info
Title
De-Identification And Privacy Issues On Bigdata Transformation
Abstract
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.
Year
DOI
Venue
2020
10.1109/BigComp48618.2020.00-14
2020 IEEE INTERNATIONAL CONFERENCE ON BIG DATA AND SMART COMPUTING (BIGCOMP 2020)
Keywords
DocType
ISSN
Big Data, Privacy, personal-information, k-anonymity, l-diversity, t-closeness
Conference
2375-933X
Citations 
PageRank 
References 
0
0.34
0
Authors
5
Name
Order
Citations
PageRank
Hyo-jun Lee100.68
Si-heon Cho200.68
Ji-won Seong300.68
Suan Lee400.68
Wookey Lee519629.22