Privacy-Preserving Inter-database Operations

We present protocols for distributed computation of relational intersections and equi-joins such that each site gains no information about the tuples at the other site that do not intersect or join with its own tuples. Such protocols form the building blocks of distributed information systems that manage sensitive information, such as patient records and financial transactions, that must be shared in only a limited manner. We discuss applications of our protocols, outlining the ramifications of assumptions such as semi-honesty. In addition to improving on the efficiency of earlier protocols, our protocols are asymmetric, making them especially applicable to applications in which a low-powered client interacts with a server in a privacy-preserving manner. We present a brief experimental study of our protocols.

[1]  Niv Gilboa,et al.  Computationally private information retrieval (extended abstract) , 1997, STOC '97.

[2]  Daniel A. Keim,et al.  Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining , 2002, KDD.

[3]  Vijay S. Iyengar,et al.  Transforming data to satisfy privacy constraints , 2002, KDD.

[4]  A. Yao,et al.  Fair exchange with a semi-trusted third party (extended abstract) , 1997, CCS '97.

[5]  Robin Milner,et al.  On Observing Nondeterminism and Concurrency , 1980, ICALP.

[6]  Tad Hogg,et al.  Protecting privacy while sharing information in electronic communities , 2000, CFP '00.

[7]  Wenliang Du,et al.  Secure multi-party computation problems and their applications: a review and open problems , 2001, NSPW '01.

[8]  David Chaum,et al.  Multiparty unconditionally secure protocols , 1988, STOC '88.

[9]  Alexandre V. Evfimievski,et al.  Privacy preserving mining of association rules , 2002, Inf. Syst..

[10]  Alexandre V. Evfimievski,et al.  Information sharing across private databases , 2003, SIGMOD '03.

[11]  Avi Wigderson,et al.  Completeness theorems for non-cryptographic fault-tolerant distributed computation , 1988, STOC '88.

[12]  Yuval Ishai,et al.  Protecting data privacy in private information retrieval schemes , 1998, STOC '98.

[13]  Chris Clifton,et al.  Secure set intersection cardinality with application to association rule mining , 2005, J. Comput. Secur..

[14]  Yehuda Lindell,et al.  Privacy Preserving Data Mining , 2000, Journal of Cryptology.

[15]  Chris Clifton,et al.  Privacy-preserving k-means clustering over vertically partitioned data , 2003, KDD '03.

[16]  Peter Winkler,et al.  Comparing information without leaking it , 1996, CACM.

[17]  John F. Canny,et al.  Collaborative filtering with privacy via factor analysis , 2002, SIGIR '02.

[18]  Chun Zhang,et al.  Storing and querying ordered XML using a relational database system , 2002, SIGMOD '02.

[19]  Mikhail J. Atallah,et al.  A secure protocol for computing dot-products in clustered and distributed environments , 2002, Proceedings International Conference on Parallel Processing.

[20]  Yehuda Lindell,et al.  Privacy Preserving Data Mining , 2002, Journal of Cryptology.

[21]  Pedro Domingos.  KDD-2003 : proceedings of the Ninth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, August 24-27, 2003, Washington, DC, USA , 2003 .

[22]  Wenliang Du,et al.  Using randomized response techniques for privacy-preserving data mining , 2003, KDD '03.

[23]  Rafail Ostrovsky,et al.  Universal service-providers for database private information retrieval (extended abstract) , 1998, PODC '98.

[24]  Tad Hogg,et al.  Enhancing privacy and trust in electronic communities , 1999, EC '99.

[25]  John F. Canny,et al.  Collaborative filtering with privacy , 2002, Proceedings 2002 IEEE Symposium on Security and Privacy.

[26]  Wenliang Du,et al.  Secure Multi-party Computational Geometry , 2001, WADS.

[27]  Yuval Ishai,et al.  Information-Theoretic Private Information Retrieval: A Unified Construction , 2001, ICALP.