使用生成对抗网络保护基于触摸的连续认证系统免受主动对手的攻击

M. Agrawal, P. Mehrotra, Rajesh Kumar, R. Shah
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引用次数: 6

摘要

先前的研究表明,通常研究的基于触摸的连续认证系统(V-TCAS)容易受到群体攻击。本文提出了一种新的生成对抗网络辅助TCAS (G-TCAS)框架,该框架对群体攻击具有更强的弹性。G-TCAS框架在117名用户的数据集上进行了测试,这些用户使用智能手机和平板电脑进行交互。平均而言,智能手机的V-TCAS错误接受率(FARs)的增幅(22%)远高于G-TCAS(13%)。同样,与片剂G-TCAS(6%)相比,V-TCAS的FARs增加了25%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Defending Touch-based Continuous Authentication Systems from Active Adversaries Using Generative Adversarial Networks
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.
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