Defending Touch-based Continuous Authentication Systems from Active Adversaries Using Generative Adversarial Networks
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Abstract (arXiv)
Previous studies have demonstrated that commonly studied (vanilla) touch-based continuous authentication systems (V-TCAS) are susceptible to population attack. This paper proposes a novel Generative Adversarial Network assisted TCAS (G-TCAS) framework, which showed more resilience to the population attack. G-TCAS framework was tested on a dataset of 117 users who interacted with a smartphone and tablet pair. On average, the increase in the false accept rates (FARs) for V-TCAS was much higher (22%) than G-TCAS (13%) for the smartphone. Likewise, the increase in the FARs for V-TCAS was 25% compared to G-TCAS (6%) for the tablet.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Builds on 6 of its 38 references that are in the map. First posted on arXiv 15 Jun 2021.
Builds on
6 of 38 references.
References · 6
- 2016Active User Authentication for Smartphones: A Challenge Data Set and Benchmark Resultscited by 10
- 2017Continuous Authentication Using One-class Classifiers and their Fusioncited by 6
- 2018Continuous Authentication of Smartphones Based on Application Usagecited by 6
- 2020On the Resilience of Biometric Authentication Systems against Random Inputscited by 6
- 2019Insights from BB-MAS -- A Large Dataset for Typing, Gait and Swipes of the Same Person on Desktop, Tablet and Phonecited by 4
- 2020On the Inference of Soft Biometrics from Typing Patterns Collected in a Multi-device Environmentcited by 2
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Citing papers per year: 2021: 1; 2022: 1; 2023: 1.
3 papers.