Privacy-Preserving data set union

Authors:
Alberto Maria Segre;Andrew Wildenberg;Veronica Vieland;Ying Zhang
Affiliations:
Department of Computer Science, The University of Iowa, Iowa City, IA;Department of Computer Science, Cornell College, Mount Vernon, IA;Columbus Children's Research Institute, Ohio State University, Columbus, OH;Program in Applied Mathematical and Computational Sciences, The University of Iowa, Iowa City, IA
Venue:
PSD'06 Proceedings of the 2006 CENEX-SDC project international conference on Privacy in Statistical Databases
Year:
2006

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Abstract

This paper describes a cryptographic protocol for merging two or more data sets without divulging those identifying records; technically, the protocol computes a blind set-theoretic union. Applications for this protocol arise, for example, in data analysis for biomedical application areas, where identifying fields (e.g., patient names) are protected by governmental privacy regulations or by institutional research board policies.