DocumentCode
247081
Title
New Data Publishing Framework in the Big Data Environments
Author
Jun Yang ; Zheli Liu ; Chunfu Jia ; Kai Lin ; Zijing Cheng
Author_Institution
Coll. of Comput. & Control Eng., Nankai Univ., Tianjin, China
fYear
2014
fDate
8-10 Nov. 2014
Firstpage
363
Lastpage
366
Abstract
The traditional data publishing methods will remove the sensitive attributes and generate the abundant records to achieve the goal of privacy protection. In the big data environment, they cannot satisfy some data mining tasks with privacy considerations. This paper provides a new data publishing framework. It can preserve the data integrity, i.e., the original data structure is preserved, and it doesn´t require deleting any attribute and adding k-times data to achieve anonymity.
Keywords
Big Data; cryptography; data integrity; data mining; data privacy; data structures; anonymity; big data environment; data integrity preservation; data mining; data publishing framework; data publishing method; data structure preservation; decyption; encyption; privacy considerations; privacy protection; Data mining; Databases; Encryption; Privacy; Publishing; data publishing; big data; format-preserving encryption; data mask;
fLanguage
English
Publisher
ieee
Conference_Titel
P2P, Parallel, Grid, Cloud and Internet Computing (3PGCIC), 2014 Ninth International Conference on
Conference_Location
Guangdong
Type
conf
DOI
10.1109/3PGCIC.2014.139
Filename
7024610
Link To Document