Privacy-Preserving Data Integration and Sharing
Download
Author
C. Clifton, M. Kantarcioglu, A. Doan, G. Schadow, J. Vaidya, A. Elmagarmid, D. Suciu
Tech report number
CERIAS TR 2004-75
Entry type
inproceedings
Abstract
Integrating data from multiple sources has been a longstanding
challenge in the database community. Techniques such as privacy-preserving data mining promises privacy,but assume data has integration has been accomplished. Data integration methods are seriously hampered by inability to share the data to be integrated. This paper lays out a
privacy framework for data integration. Challenges for data
integration in the context of this framework are discussed,in the context of existing accomplishments in data integration. Many of these challenges are opportunities for the data mining community
Download
Date
2004 – 06 – 13
Journal
Proceedings of the 9th ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery (DMKD 2004)
Key alpha
Clifton
Publication Date
2004-06-13
Contents
1. INTRODUCTION
2. MOTIVATION
3. DATA INTEGRATION AND DATA MINING
4. PRIVACY PRESERVATION CHALLENGES
5. CONCLUSION
Copyright
2004 ACM
Language
English
Location
A hard-copy of this is in the CERIAS Library
Subject
Data-integration and Sharing

