Morellian Analysis for Browsers: Making Web Authentication Stronger with Canvas Fingerprinting
Résumé
In this paper, we present the first fingerprinting-based authen-tication scheme that is not vulnerable to trivial replay attacks. Our proposed canvas-based fingerprinting technique utilizes one key characteristic: it is parameterized by a challenge, generated on the server side. We perform an in-depth analysis of all parameters that can be used to generate canvas challenges , and we show that it is possible to generate unique, unpredictable, and highly diverse canvas-generated images each time a user logs onto a service. With the analysis of images collected from more than 1.1 million devices in a real-world large-scale experiment, we evaluate our proposed scheme against a large set of attack scenarios and conclude that canvas fingerprinting is a suitable mechanism for stronger authentication on the web.
Domaines
Cryptographie et sécurité [cs.CR]Origine | Fichiers produits par l'(les) auteur(s) |
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