Privacy-Preserving Hypothesis Testing for the Analysis of Epidemiological Medical Data

This paper studies privacy issues related to epidemiological studies. Epidemiological studies need to preserve the privacy of subjects because they use personal information. Thus, privacy is preserved using a secure scalar product protocol based on a public-key cryptosystem and the secure function evaluation. However, the secure function evaluation has performance limitations in evaluating a product and a squared root. Therefore, this paper proposes a new computationally efficient scheme for privacy-preserving epidemiological analysis. The performance and the security of the proposed scheme are evaluated based on its trial implementation.