Efficient Determination of Equivalence for Encrypted Data

Jason N. Doctor, Jaideep Vaidya, Xiaoqian Jiang, Shuang Wang, Lisa M. Schilling, Toan Ong, Michael E. Matheny, Lucila Ohno-Machado, Daniella Meeker

Secure computation of equivalence has fundamental application in many different areas, including healthcare. We study this problem in the context of matching an individual identity to link medical records across systems. We develop an efficient solution for equivalence based on existing work that can evaluate the greater than relation. We implement the approach and demonstrate its effectiveness on data, as well as demonstrate how it meets regulatory criteria for risk.

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