vix.ing · top · new · best · stats · spec

A Practical Deep Learning-Based Acoustic Side Channel Attack on Keyboards

2023/07/01 by Joshua Harrison, Ehsan Toreini, Maryam Mehrnezhad · 17 voices
Computer Science · #Advanced Malware Detection Techniques #Cryptographic Implementations and Security #User Authentication and Security Systems #cs.CR #cs.LG

paper · pdf · doi:10.1109/eurospw59978.2023.00034

openalex publication_date 2023/07/01 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/29

Abstract

With recent developments in deep learning, the ubiquity of microphones and the rise in online services via personal devices, acoustic side channel attacks present a greater threat to keyboards than ever. This paper presents a practical implementation of a state-of-the-art deep learning model in order to classify laptop keystrokes, using a smartphone integrated microphone. When trained on keystrokes recorded by a nearby phone, the classifier achieved an accuracy of 95%, the highest accuracy seen without the use of a language model. When trained on keystrokes recorded using the video-conferencing software Zoom, an accuracy of 93% was achieved, a new best for the medium. Our results prove the practicality of these side channel attacks via off-the-shelf equipment and algorithms. We discuss a series of mitigation methods to protect users against these series of attacks.

Citations

Discussions

Related