Morellian Analysis for Browsers: Making Web Authentication Stronger with Canvas Fingerprinting - Archive ouverte HAL Access content directly
Book Sections Year : 2019

Morellian Analysis for Browsers: Making Web Authentication Stronger with Canvas Fingerprinting

Abstract

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.
Fichier principal
Vignette du fichier
canvasauthentication_dimva2019.pdf (1.28 Mo) Télécharger le fichier
Origin : Files produced by the author(s)
Loading...

Dates and versions

hal-02881632 , version 1 (26-06-2020)

Identifiers

Cite

Pierre Laperdrix, Gildas Avoine, Benoit Baudry, Nick Nikiforakis. Morellian Analysis for Browsers: Making Web Authentication Stronger with Canvas Fingerprinting. Detection of Intrusions and Malware, and Vulnerability Assessment - 16th International Conference, {DIMVA} 2019, Gothenburg, Sweden, June 19-20, 2019, Proceedings, pp.43-66, 2019, ⟨10.1007/978-3-030-22038-9_3⟩. ⟨hal-02881632⟩
142 View
420 Download

Altmetric

Share

Gmail Facebook X LinkedIn More