听力手表:可穿戴式双因素认证,使用语音信号抵御近距离攻击

Prakash Shrestha, Nitesh Saxena
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引用次数: 22

摘要

减少传统的双因素身份验证(TFA)所涉及的用户工作量是一个重要的研究课题。最近在这个方向上的努力利用环境声音来检测第二因素设备(电话)和登录终端(浏览器)之间的接近程度,并且消除了用户传输PIN码的需要。这种方法是高度可用的,但完全容易受到近距离攻击者的攻击,即那些远程定位并可以猜测受害者的音频环境或使手机产生可预测的声音(例如,铃声)的攻击者,以及那些在物理上接近用户的攻击者。在本文中,我们提出了一种基于可穿戴设备(手表/手环)和主动浏览器生成随机语音的新型TFA机制listen - watch。当用户尝试登录时,浏览器会将一个短的随机代码编码为语音,如果手表的音频记录包含此代码(使用语音识别解码),并且与浏览器的音频记录足够相似,则登录成功。远程攻击者,谁已经猜到用户的环境或创建可预测的电话/手表的声音,将被击败,因为身份验证的成功依赖于手表的录音中的随机代码的存在。近距离攻击者也会被击败,除非它离手表非常近,因为可穿戴麦克风通常被设计成只能接收附近的声音(例如语音命令)。此外,由于使用了可穿戴的第二因素设备,即使从手机登录,listen - watch自然也能实现双重安全。我们的贡献有三方面。首先,我们介绍了基于可穿戴设备、主动语音和语音识别的强而低功耗TFA的思想,从而产生了对远程和近距离攻击者都安全的监听-监视系统。其次,我们为Android智能手表(以及配套的智能手机)和Chrome浏览器设计并实现了Listening-Watch,而不需要任何浏览器插件。第三,我们评估listen - watch在良性和敌对设置下的身份验证错误。我们的结果表明,在适当的阈值化和扬声器音量水平的基础上,listen - watch可以在两种设置中产生最小的错误。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Listening Watch: Wearable Two-Factor Authentication using Speech Signals Resilient to Near-Far Attacks
Reducing the level of user effort involved in traditional two-factor authentication (TFA) constitutes an important research topic. A recent effort in this direction leverages ambient sounds to detect the proximity between the second factor device (phone) and the login terminal (browser), and eliminates the need for the user to transfer PIN codes. This approach is highly usable, but is completely vulnerable against far-near attackers, i.e., ones who are remotely located and can guess the victim's audio environment or make the phone create predictable sounds (e.g., ringers), and those who are in physical proximity of the user. In this paper, we propose Listening-Watch, a new TFA mechanism based on a wearable device (watch/bracelet) and active browser-generated random speech sounds. As the user attempts to login, the browser populates a short random code encoded into speech, and the login succeeds if the watch's audio recording contains this code (decoded using speech recognition), and is similar enough to the browser's audio recording. The remote attacker, who has guessed the user's environment or created predictable phone/watch sounds, will be defeated since authentication success relies upon the presence of the random code in watch's recordings. The proximity attacker will also be defeated unless it is extremely close to the watch, since the wearable microphones are usually designed to be only capable of picking up nearby sounds (e.g., voice commands). Furthermore, due to the use of a wearable second factor device, Listening-Watch naturally enables two-factor security even when logging in from a mobile phone. Our contributions are three-fold. First, we introduce the idea of strong and low-effort TFA based on wearable devices, active speech sounds and speech recognition, giving rise to the Listening-Watch system that is secure against both remote and proximity attackers. Second, we design and implement Listening-Watch for an Android smartwatch (and companion smartphone) and the Chrome browser, without the need for any browser plugins. Third, we evaluate Listening-Watch for authentication errors in both benign and adversarial settings. Our results show that Listening-Watch can result in minimal errors in both settings based on appropriate thresholdization and speaker volume levels.
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