Secure multi-party computation problems and their applications: a review and open problems
Proceedings of the 2001 workshop on New security paradigms
Protecting Respondents' Identities in Microdata Release
IEEE Transactions on Knowledge and Data Engineering
Tools for privacy preserving distributed data mining
ACM SIGKDD Explorations Newsletter
k-anonymity: a model for protecting privacy
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Privacy-Preserving Distributed Mining of Association Rules on Horizontally Partitioned Data
IEEE Transactions on Knowledge and Data Engineering
Privacy-Preserving Data Mining: Why, How, and When
IEEE Security and Privacy
Privacy-enhancing k-anonymization of customer data
Proceedings of the twenty-fourth ACM SIGMOD-SIGACT-SIGART symposium on Principles of database systems
Data Mining: Concepts and Techniques
Data Mining: Concepts and Techniques
Mondrian Multidimensional K-Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
\ell -Diversity: Privacy Beyond \kappa -Anonymity
ICDE '06 Proceedings of the 22nd International Conference on Data Engineering
A secure distributed framework for achieving k-anonymity
The VLDB Journal — The International Journal on Very Large Data Bases
M-invariance: towards privacy preserving re-publication of dynamic datasets
Proceedings of the 2007 ACM SIGMOD international conference on Management of data
DObjects: Enabling Distributed Data Services for Metacomputing Platforms
ICCS '08 Proceedings of the 8th international conference on Computational Science, Part I
Privacy preserving serial data publishing by role composition
Proceedings of the VLDB Endowment
Privacy-preserving data publishing: A survey of recent developments
ACM Computing Surveys (CSUR)
Centralized and Distributed Anonymization for High-Dimensional Healthcare Data
ACM Transactions on Knowledge Discovery from Data (TKDD)
Anonymity meets game theory: secure data integration with malicious participants
The VLDB Journal — The International Journal on Very Large Data Bases
Secure distributed computation of anonymized views of shared databases
ACM Transactions on Database Systems (TODS)
Distributed data federation without disclosure of user existence
DBSec'12 Proceedings of the 26th Annual IFIP WG 11.3 conference on Data and Applications Security and Privacy
Secure distributed framework for achieving ε-differential privacy
PETS'12 Proceedings of the 12th international conference on Privacy Enhancing Technologies
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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.