Abstract
There is an increasing need for sharing data repositories containing personal information across multiple distributed and private databases. However, such data sharing is subject to constraints imposed by privacy of individuals or data subjects as well as data confidentiality of institutions or data providers. Concretely, given a query spanning multiple databases, query results should not contain individually identifiable information. In addition, institutions should not reveal their databases to each other apart from the query results. In this paper, we develop a set of decentralized protocols that enable data sharing for horizontally partitioned databases given these constraints. Our approach includes a new notion, l-site-diversity, for data anonymization to ensure anonymity of data providers in addition to that of data subjects, and a distributed anonymization protocol that allows independent data providers to build a virtual anonymized database while maintaining both privacy constraints. © 2009 Springer Berlin Heidelberg.
Cite
CITATION STYLE
Jurczyk, P., & Xiong, L. (2009). Distributed anonymization: Achieving privacy for both data subjects and data providers. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5645 LNCS, pp. 191–207). https://doi.org/10.1007/978-3-642-03007-9_13
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