English

Keystroke Detection by Exploiting Unintended RF Emission from Repaired USB Keyboards

Cryptography and Security 2025-09-03 v1

Abstract

Electronic devices and cables inadvertently emit RF emissions as a byproduct of signal processing and/or transmission. Labeled as electromagnetic emanations, they form an EM side-channel for data leakage. Previously, it was believed that such leakage could be contained within a facility since they are weak signals with a short transmission range. However, in the preliminary version of this work [1], we found that the traditional cable repairing process forms a tiny monopole antenna that helps emanations transmit over a long range. Experimentation with three types of cables revealed that emanations from repaired cables remain detectable even at >4 m and can penetrate a 14 cm thick concrete wall. In this extended version, we show that such emanation can be exploited at a long distance for information extraction by detecting keystrokes typed on a repaired USB keyboard. By collecting data for 70 different keystrokes at different distances from the target in 3 diverse environments (open space, a corridor outside an office room, and outside a building) and developing an efficient detection algorithm, ~100% keystroke detection accuracy has been achieved up to 12 m distance, which is the highest reported accuracy at such a long range for USB keyboards in the literature. The effect of two experimental factors, interference and human-body coupling, has been investigated thoroughly. Along with exploring the vulnerability, multi-layer external metal shielding during the repairing process as a possible remedy has been explored. This work exposes a new attack surface caused by hardware modification, its exploitation, and potential countermeasures.

Keywords

Cite

@article{arxiv.2509.00043,
  title  = {Keystroke Detection by Exploiting Unintended RF Emission from Repaired USB Keyboards},
  author = {Md Faizul Bari and Yi Xie and Meghna Roy Choudhury and Shreyas Sen},
  journal= {arXiv preprint arXiv:2509.00043},
  year   = {2025}
}

Comments

This journal version is an extended version of a previously published conference paper which can be found here: https://ieeexplore.ieee.org/abstract/document/10181751

R2 v1 2026-07-01T05:12:41.175Z