# Capacitive Touchscreens at Risk: Recovering Handwritten Trajectory on Smartphone via Electromagnetic Emanations

arXiv: https://arxiv.org/abs/2512.11484 · HTML: https://mlsanity.com/paper/2512.11484/

## Key facts

- No citing papers in the map yet (data through 14 Oct 2026).
- Builds on 2 of its 22 references that are in the map.
- First posted on arXiv 12 Dec 2025.

## Builds on (most cited first, 2 of 2)

- [Screen Gleaning: A Screen Reading TEMPEST Attack on Mobile Devices Exploiting an Electromagnetic Side Channel](https://mlsanity.com/paper/2011.09877/) (2020)
- [PIN Skimming: Exploiting the Ambient-Light Sensor in Mobile Devices](https://mlsanity.com/paper/1405.3760/) (2014)

## Abstract (arXiv)

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.