DocumentCode
2496209
Title
On syntactic anonymity and differential privacy
Author
Clifton, C. ; Tassa, Tamir
Author_Institution
Dept. of Comput. Sci., Purdue Univ., West Lafayette, IN, USA
fYear
2013
fDate
8-12 April 2013
Firstpage
88
Lastpage
93
Abstract
Recently, there has been a growing debate over approaches for handling and analyzing private data. Research has identified issues with syntactic anonymity models. Differential privacy has been promoted as the answer to privacy-preserving data mining. We discuss here issues involved and criticisms of both approaches, and conclude that both have their place. We identify research directions that will enable greater access to data while improving privacy guarantees.
Keywords
data mining; data privacy; differential privacy; privacy preserving data mining; private data analysis; syntactic anonymity models; Data models; Data privacy; Noise; Privacy; Publishing; Syntactics;
fLanguage
English
Publisher
ieee
Conference_Titel
Data Engineering Workshops (ICDEW), 2013 IEEE 29th International Conference on
Conference_Location
Brisbane, QLD
Print_ISBN
978-1-4673-5303-8
Electronic_ISBN
978-1-4673-5302-1
Type
conf
DOI
10.1109/ICDEW.2013.6547433
Filename
6547433
Link To Document