通过非接触式无线充电侧通道揭示智能手机上的用户交互

Tao Ni, Xiaokuan Zhang, Chaoshun Zuo, Jianfeng Li, Zhenyu Yan, Wubing Wang, Weitao Xu, Xiapu Luo, Qingchuan Zhao
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引用次数: 2

摘要

如今,越来越多的智能手机支持无线充电,利用电磁感应将电力从无线充电器传输到充电的智能手机。在本文中,我们报告了一种新的非接触式和上下文感知的无线充电侧信道攻击,该攻击捕获了无线充电过程中产生的两种物理现象(即线圈啸叫和磁场扰动),并进一步推断出充电智能手机上的用户交互。我们设计并实现了一个被称为WISERS的三阶段攻击框架,以证明这种新的侧信道的实用性。WISERS首先捕获线圈啸叫和无线充电器发出的磁场扰动,然后推断出(i)接口间切换(例如,从主屏幕切换到应用程序界面)和(ii)接口内活动(例如,应用程序内部的键盘输入),以构建用户交互上下文,并进一步揭示敏感信息。我们广泛评估WISERS与流行的智能手机和商用现货(COTS)无线充电器的有效性。我们的评估结果表明,WISERS在推断屏幕解锁密码和应用启动等敏感信息方面的准确率可以达到90.4%以上。此外,我们的研究还表明,WISERS对一系列影响因素具有弹性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Uncovering User Interactions on Smartphones via Contactless Wireless Charging Side Channels
Today, there is an increasing number of smartphones supporting wireless charging that leverages electromagnetic induction to transmit power from a wireless charger to the charging smartphone. In this paper, we report a new contactless and context-aware wireless-charging side-channel attack, which captures two physical phenomena (i.e., the coil whine and the magnetic field perturbation) generated during this wireless charging process and further infers the user interactions on the charging smartphone. We design and implement a three-stage attack framework, dubbed WISERS, to demonstrate the practicality of this new side channel. WISERS first captures the coil whine and the magnetic field perturbation emitted by the wireless charger, then infers (i) inter-interface switches (e.g., switching from the home screen to an app interface) and (ii) intra-interface activities (e.g., keyboard inputs inside an app) to build user interaction contexts, and further reveals sensitive information. We extensively evaluate the effectiveness of WISERS with popular smartphones and commercial-off-the-shelf (COTS) wireless chargers. Our evaluation results suggest that WISERS can achieve over 90.4% accuracy in inferring sensitive information, such as screen-unlocking passcode and app launch. In addition, our study also shows that WISERS is resilient to a list of impact factors.
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