Young Researcher Paper Award 2023
🥇Winners

Notice of retraction
Vol. 34, No. 8(3), S&M3042

Notice of retraction
Vol. 32, No. 8(2), S&M2292

Print: ISSN 0914-4935
Online: ISSN 2435-0869
Sensors and Materials
is an international peer-reviewed open access journal to provide a forum for researchers working in multidisciplinary fields of sensing technology.
Sensors and Materials
is covered by Science Citation Index Expanded (Clarivate Analytics), Scopus (Elsevier), and other databases.

Instructions to authors
English    日本語

Instructions for manuscript preparation
English    日本語

Template
English

Publisher
 MYU K.K.
 Sensors and Materials
 1-23-3-303 Sendagi,
 Bunkyo-ku, Tokyo 113-0022, Japan
 Tel: 81-3-3827-8549
 Fax: 81-3-3827-8547

MYU Research, a scientific publisher, seeks a native English-speaking proofreader with a scientific background. B.Sc. or higher degree is desirable. In-office position; work hours negotiable. Call 03-3827-8549 for further information.


MYU Research

(proofreading and recording)


MYU K.K.
(translation service)


The Art of Writing Scientific Papers

(How to write scientific papers)
(Japanese Only)

Sensors and Materials, Volume 36, Number 10(3) (2024)
Copyright(C) MYU K.K.
pp. 4519-4534
S&M3815 Research Paper of Special Issue
https://doi.org/10.18494/SAM5237
Published: October 29, 2024

WatchLogger: Keystroke Detection and Recognition of Typed Words Using Smartwatch [PDF]

Gangkai Li, Yugo Nakamura, Hyuckjin Choi, Shogo Fukushima, and Yutaka Arakawa

(Received July 16, 2024; Accepted September 17, 2024)

Keywords: smartwatch, wearable sensor, keystroke detection, word classification, side-channel attack

Nowadays, more and more people are wearing smartwatches in their daily lives. The various sensors embedded in smartwatches bring the ability to evaluate users’ status as well as the risk of privacy issues. For example, if users are typing on keyboards while wearing smartwatches, the attacker can know the typed contents from the sensor data collected by the malicious applications that are installed on the targets’ smartwatches. In this paper, we propose WatchLogger, a framework using audio and accelerometer signals to recognize the English words being typed, to demonstrate how to implement the smartwatch-based side-channel attack. In contrast with previous studies that focused on the recognition of each key or pair of keys being pressed, WatchLogger aims to perform recognition on the scale of words. To achieve this goal, WatchLogger exploits the audio signals for segmentation and the accelerometer signals for classification. In addition, we propose an ensemble classification model to deal with the problem caused by too many words. Finally, we build the WTW-100 dataset (Wearable Typed Words dataset with 100 classes of words) using data from four participants and conduct experiments on the basis of this dataset. The experimental results show accuracies of 98.31 and 99.62% and F1 scores of 0.9745 and 0.9855 for keystroke detection and classification, respectively, and an accuracy of 79.76% for word classification, indicating a considerable performance of WatchLogger.

Corresponding author: Gangkai Li


Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 International License.

Cite this article
Gangkai Li, Yugo Nakamura, Hyuckjin Choi, Shogo Fukushima, and Yutaka Arakawa, WatchLogger: Keystroke Detection and Recognition of Typed Words Using Smartwatch, Sens. Mater., Vol. 36, No. 10, 2024, p. 4519-4534.



Forthcoming Regular Issues


Forthcoming Special Issues

Applications of Novel Sensors and Related Technologies for Internet of Things
Guest editor, Teen-Hang Meen (National Formosa University), Wenbing Zhao (Cleveland State University), and Cheng-Fu Yang (National University of Kaohsiung)
Call for paper


Special Issue on Advanced Sensing Technologies for Green Energy
Guest editor, Yong Zhu (Griffith University)
Call for paper


Special Issue on Room-temperature-operation Solid-state Radiation Detectors
Guest editor, Toru Aoki (Shizuoka University)
Call for paper


Special Issue on International Conference on Biosensors, Bioelectronics, Biomedical Devices, BioMEMS/NEMS and Applications 2023 (Bio4Apps 2023)
Guest editor, Dzung Viet Dao (Griffith University) and Cong Thanh Nguyen (Griffith University)
Conference website
Call for paper


Special Issue on Advanced Sensing Technologies and Their Applications in Human/Animal Activity Recognition and Behavior Understanding
Guest editor, Kaori Fujinami (Tokyo University of Agriculture and Technology)
Call for paper


Special Issue on Piezoelectric Thin Films and Piezoelectric MEMS
Guest editor, Isaku Kanno (Kobe University)
Call for paper


Copyright(C) MYU K.K. All Rights Reserved.