Imaging privacy threats from an ambient light sensor.

ABSTRACT: Embedded sensors in smart devices pose privacy risks, often unintentionally leaking user information. We investigate how combining an ambient light sensor with a device display can capture an image of touch interaction without a camera. By displaying a known video sequence, we use the light sensor to capture reflected light intensity variations partially blocked by the touching hand, formulating an inverse problem similar to single-pixel imaging. Because of the sensors' heavy quantization and low sensitivity, we propose an inversion algorithm involving an ℓ_p-norm dequantizer and a deep denoiser as natural image priors, to reconstruct images from the screen's perspective. We demonstrate touch interactions and eavesdropping hand gestures on an off-the-shelf Android t

SUBMITTER: Liu Y 

PROVIDER: S-EPMC10780887 | biostudies-literature | 2024 Jan

REPOSITORIES: biostudies-literature