The Curious Case of the Curious Case: Detecting Touchscreen Events Using a Smartphone Protective Case

Gluck, Tomer; Puzis, Rami; Oren, Yossi; Shabtai, Asaf

doi:10.1109/eurospw.2017.58

Cited by 1 publication

(1 citation statement)

References 3 publications

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“…To prevent eavesdropping, one approach is to use advanced materials to reduce noises (i.e., coil whine) and shield the magnetic field to a certain degree, making them hard to be measured. Unfortunately, this approach may not be applied to existing products, and its effectiveness needs further investigation, let alone its cost-benefit [26]. Hence, we suggest complementing this approach with proactive protection methods.…”

Section: Discussionmentioning

confidence: 99%

Uncovering User Interactions on Smartphones via Contactless Wireless Charging Side Channels

Zhang

Zuo

et al. 2023

2023 IEEE Symposium on Security and Privacy (SP)

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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 threestage 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-theshelf (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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Section: Discussionmentioning

confidence: 99%