通过电磁泄漏还原手机手写轨迹，实现非接触攻击
Capacitive Touchscreens at Risk: Recovering Handwritten Trajectory on Smartphone via Electromagnetic Emanations
- 利用触摸屏电磁信号反推手写二维轨迹
- 在真实场景下达到77%字符识别率和0.74相似度
- 适合研究移动设备侧信道攻击的学者与安全人员
本文揭示并利用了一项关键安全漏洞：电容式触摸屏的电磁（EM）旁道泄露了足够信息，可恢复精细连续的手写轨迹。我们提出非接触式攻击框架TESLA，能够实时捕获屏幕书写时产生的电磁信号，并将其回归为二维手写轨迹。对多种商用智能手机的广泛评估显示，TESLA在真实攻击条件下实现了77%的字符识别准确率和0.74的杰卡德指数，表明其能恢复高度可辨识、接近原始手写的运动轨迹。
原文摘要 · Abstract (English)
This paper reveals and exploits a critical security vulnerability: the electromagnetic (EM) side channel of capacitive touchscreens leaks sufficient information to recover fine-grained, continuous handwriting trajectories. We present Touchscreen Electromagnetic Side-channel Leakage Attack (TESLA), a non-contact attack framework that captures EM signals generated during on-screen writing and regresses them into two-dimensional (2D) handwriting trajectories in real time. Extensive evaluations across a variety of commercial off-the-shelf (COTS) smartphones show that TESLA achieves 77% character recognition accuracy and a Jaccard index of 0.74, demonstrating its capability to recover highly recognizable motion trajectories that closely resemble the original handwriting under realistic attack conditions.
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