A comprehensive framework enabling data-minimizing authentication

Abstract

Classical authentication mechanisms have various drawbacks such as the weak security properties they achieve, users' privacy, service providers' data quality, and the necessary protection of the collected data. Credential-based authentication is a first step towards overcoming these drawbacks. When used with anonymous credentials, the personal data disclosed can be reduced to the minimum with respect to a business purpose while improving the assurance of the communicated data. However, this privacy-preserving combination of technologies is not used today. One reason for this lack of adoption is that a comprehensive framework for privacy-enhancing credential-based authentication is not available. In this paper we review the different components of such an authentication framework and show that one remaining missing piece is a translation between high-level authentication policies and the cryptographic token specification level. We close this gap by (1) proposing an adequate claim language specifying which certified data a user wants to reveal to satisfy a policy and by (2) providing translation algorithms for generating the anonymous credentials (cryptographic tokens) providing the data to be revealed. For the latter we consider the Identity Mixer and the U-Prove technologies, where we provide detailed translation instructions for the former.