PrintSpy: Pixel-Level Eavesdropping on Commodity Laser Printers via Electromagnetic Side Channels
Wenhao Li, Jiarong Yang, Mingda Han, Xiuzhen Cheng, Pengfei Hu, Cong Wang
摘要
Laser printers are among the most widely used output devices, serving as the final gateway for sensitive information to transition from the digital domain to physical media. However, the high-speed switching of the laser diode and the complex driving of the scanning system inevitably generate electromagnetic emissions. While traditionally regarded merely as byproducts of electromagnetic compatibility, these signals in fact carry information closely correlated with printed content, thus forming a potential physical-layer side channel. This paper presents PrintSpy, an EM side-channel analysis framework capable of non-intrusive, pixel-level reconstruction of printed content. PrintSpy establishes a cross-domain mapping mechanism that converts one-dimensional temporal EM waveforms into two-dimensional pixel matrices through energybased signal modeling and anchor-based projection, enabling robust alignment between temporal samples and printed pixels for high-fidelity page reconstruction. To address structural degradation under low signal-to-noise ratios, we further design a dual-constraint conditional diffusion model that jointly incorporates pixel priors and projection-consistency guidance to reconstruct fine-grained textures and stroke structures under noise-dominated degradation. Experimental results on multiple consumer-grade printers and real-world environments demonstrate that PrintSpy achieves stable and quantifiable content recovery, with an average character error rate below 17.91 % and reconstructable font sizes down to 6.5 pt.
问问这篇 Paper
问问你的智能体。
Lune 读过与它相关的顶会 Paper,每个回答都会注明依据哪几篇。
相关 Paper
- EMIRIS: Eavesdropping on Iris Information via Electromagnetic Side ChannelWenhao Li, Jiahao Wang, Guoming Zhang, Yanni Yang 等NDSS 2025
- WaveSpy: Remote and Through-wall Screen Attack via mmWave SensingZhengxiong Li, Fenglong Ma, Aditya Singh Rathore, Zhuolin Yang 等S&P 2020 · 被引用 40 次
- Periscope: A Keystroke Inference Attack Using Human Coupled Electromagnetic EmanationsWenqiang Jin, Srinivasan Murali, Huadi Zhu, Ming LiCCS 2021 · 被引用 34 次
- Injected and Leaked: Actively Inducing Side-Channel Leakage Using Electromagnetic Injection and Hardware NonlinearityHaoran Yan, Ziyu Shao, Shuhao Zhang, Qinhong Jiang 等USENIX Security 2026
- My Smartphone Knows What You Print: Exploring Smartphone-based Side-channel Attacks Against 3D PrintersChen Song, Feng Lin, Zhongjie Ba, Kui Ren 等CCS 2016 · 被引用 122 次
