Title :
On syntactic anonymity and differential privacy
Author :
Clifton, C. ; Tassa, Tamir
Author_Institution :
Dept. of Comput. Sci., Purdue Univ., West Lafayette, IN, USA
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;
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
DOI :
10.1109/ICDEW.2013.6547433
