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Main Authors: Huang, Yong, Lu, Yanzhao, Chen, Mingyang, Zhang, En, Li, Jiazi, Tu, Wanqing
Format: Preprint
Published: 2026
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Online Access:https://arxiv.org/abs/2604.06729
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author Huang, Yong
Lu, Yanzhao
Chen, Mingyang
Zhang, En
Li, Jiazi
Tu, Wanqing
author_facet Huang, Yong
Lu, Yanzhao
Chen, Mingyang
Zhang, En
Li, Jiazi
Tu, Wanqing
contents In video conferencing, human faces serve as the primary visual focal points, playing multifaceted roles that enhance visual communication and emotional connection. However, we argue that a human face is also a side channel, which can unwittingly leak on-screen information through online video feeds. To demonstrate this, we conduct feasibility studies, which reveal that, illuminated by both ambient light and light emitted from displays, the human face can reflect optical variations of different on-screen content. The paper then proposes FaceTell, a novel side-channel attack system that eavesdrops on fine-grained application activities from pervasive yet subtle facial reflections during video conferencing. We implement FaceTell in a real-world testbed with three different brands of laptops and four mainstream video conferencing platforms. FaceTell is then evaluated with 24 human subjects across 13 unique indoor environments. With more than 12 hours of video data, FaceTell achieves a high accuracy of 99.32% for eavesdropping on 28 popular applications and is resilient to many practical impact factors. Finally, potential countermeasures are proposed to mitigate this new attack.
format Preprint
id arxiv_https___arxiv_org_abs_2604_06729
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Turn Your Face Into An Attack Surface: Screen Attack Using Facial Reflections in Video Conferencing
Huang, Yong
Lu, Yanzhao
Chen, Mingyang
Zhang, En
Li, Jiazi
Tu, Wanqing
Cryptography and Security
In video conferencing, human faces serve as the primary visual focal points, playing multifaceted roles that enhance visual communication and emotional connection. However, we argue that a human face is also a side channel, which can unwittingly leak on-screen information through online video feeds. To demonstrate this, we conduct feasibility studies, which reveal that, illuminated by both ambient light and light emitted from displays, the human face can reflect optical variations of different on-screen content. The paper then proposes FaceTell, a novel side-channel attack system that eavesdrops on fine-grained application activities from pervasive yet subtle facial reflections during video conferencing. We implement FaceTell in a real-world testbed with three different brands of laptops and four mainstream video conferencing platforms. FaceTell is then evaluated with 24 human subjects across 13 unique indoor environments. With more than 12 hours of video data, FaceTell achieves a high accuracy of 99.32% for eavesdropping on 28 popular applications and is resilient to many practical impact factors. Finally, potential countermeasures are proposed to mitigate this new attack.
title Turn Your Face Into An Attack Surface: Screen Attack Using Facial Reflections in Video Conferencing
topic Cryptography and Security
url https://arxiv.org/abs/2604.06729