Evoking Comprehensive Mental Models of Anonymous Credentials - Open Problems in Network Security Access content directly
Conference Papers Year : 2012

Evoking Comprehensive Mental Models of Anonymous Credentials

Erik Wästlund
  • Function : Author
  • PersonId : 1003314
Julio Angulo
  • Function : Author
  • PersonId : 997970
Simone Fischer-Hübner
  • Function : Author
  • PersonId : 997967

Abstract

Anonymous credentials are a fundamental technology for preserving end users’ privacy by enforcing data minimization for online applications. However, the design of user-friendly interfaces that convey their privacy benefits to users is still a major challenge. Users are still unfamiliar with the new and rather complex concept of anonymous credentials, since no obvious real-world analogies exists that can help them create the correct mental models. In this paper we explore different ways in which suitable mental models of the data minimization property of anonymous credentials can be evoked on end users. To achieve this, we investigate three different approaches in the context of an e-shopping scenario: a card-based approach, an attribute-based approach and an adapted card-based approach. Results show that the adapted card-based approach is a good approach towards evoking the right mental models for anonymous credential applications. However, better design paradigms are still needed to make users understand that attributes can be used to satisfy conditions without revealing the value of the attributes themselves.
Fichier principal
Vignette du fichier
978-3-642-27585-2_1_Chapter.pdf (610.83 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01481502 , version 1 (02-03-2017)

Licence

Attribution

Identifiers

Cite

Erik Wästlund, Julio Angulo, Simone Fischer-Hübner. Evoking Comprehensive Mental Models of Anonymous Credentials. International Workshop on Open Problems in Network Security (iNetSec), Jun 2011, Lucerne, Switzerland. pp.1-14, ⟨10.1007/978-3-642-27585-2_1⟩. ⟨hal-01481502⟩
113 View
152 Download

Altmetric

Share

Gmail Facebook X LinkedIn More