Defending Touch-based Continuous Authentication Systems from Active Adversaries Using Generative Adversarial Networks
This addresses security risks for smartphone and tablet users by improving resilience against active adversaries, though it is an incremental enhancement to existing authentication methods.
The paper tackled the vulnerability of touch-based continuous authentication systems to population attacks by proposing a Generative Adversarial Network-assisted framework, which reduced false accept rate increases to 13% on smartphones and 6% on tablets compared to 22% and 25% for vanilla systems.
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.