监听按键与毫米级别的音频范围在一个单一的电话

Jian Liu, Yan Wang, Gorkem Kar, Yingying Chen, J. Yang, M. Gruteser
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引用次数: 141

摘要

本文探讨了在击键窥探场景的背景下,移动设备上音频测距的限制。声学击键窥探是具有挑战性的,因为它需要区分和标记由非常接近的数十个键产生的声音。现有的声学击键识别工作依赖于标签数据、语言环境或键盘周围放置的多部手机的训练,这些要求限制了在对抗环境中的实用性。在这项工作中,我们展示了移动音频硬件的进步可以用来区分毫米级别的位置差异,这使得仅从键盘后面的单个手机定位击键的起源成为可能。该技术利用到达测量的时间差和声学特征对击键进行聚类,以识别同一键的多个击键。然后,它会计算这些声音的来源,精确到足以识别和标记每个键。通过定位击键,该技术避免了对标记训练数据或语言上下文的需要。用三种类型的键盘和现成的智能手机进行的实验表明,我们的系统可以恢复94%的按键,据我们所知,这是第一个能够对密码进行声学窥探的单设备技术。
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Snooping Keystrokes with mm-level Audio Ranging on a Single Phone
This paper explores the limits of audio ranging on mobile devices in the context of a keystroke snooping scenario. Acoustic keystroke snooping is challenging because it requires distinguishing and labeling sounds generated by tens of keys in very close proximity. Existing work on acoustic keystroke recognition relies on training with labeled data, linguistic context, or multiple phones placed around a keyboard --- requirements that limit usefulness in an adversarial context. In this work, we show that mobile audio hardware advances can be exploited to discriminate mm-level position differences and that this makes it feasible to locate the origin of keystrokes from only a single phone behind the keyboard. The technique clusters keystrokes using time-difference of arrival measurements as well as acoustic features to identify multiple strokes of the same key. It then computes the origin of these sounds precise enough to identify and label each key. By locating keystrokes this technique avoids the need for labeled training data or linguistic context. Experiments with three types of keyboards and off-the-shelf smartphones demonstrate scenarios where our system can recover $94\%$ of keystrokes, which to our knowledge, is the first single-device technique that enables acoustic snooping of passwords.
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