Blind Transfer of Personal Data Achieving Privacy

Alexis Bonnecaze () and Robert Rolland ()
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Alexis Bonnecaze: CNRS
Robert Rolland: CNRS

A chapter in Computational Mathematics and Variational Analysis, 2020, pp 25-32 from Springer

Abstract: Abstract Exploitation of data for statistical or economic analyses is an important and rapidly growing area. In this article, we address the problem of privacy when data containing sensitive information are processed by a third party. In order to solve this problem, we propose a cryptographic protocol and we prove its security. The security analysis leads to introduce the new notion of generalized discrete logarithm problem. Our protocol has effectively been deployed within a network of more than 5000 pharmacies.

Keywords: Privacy; Hash function; Elliptic curve ElGamal ciphering; Generalized discrete logarithm problem (search for similar items in EconPapers)
Date: 2020
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Persistent link: https://EconPapers.repec.org/RePEc:spr:spochp:978-3-030-44625-3_2

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DOI: 10.1007/978-3-030-44625-3_2

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