Inferring Smartphone Users’ Handwritten Patterns by using Motion Sensors

Wei-Han Lee, Jorge Ortiz, Bongjun Ko, Ruby Lee

2018

Abstract

Mobile devices including smartphones and wearable devices are increasingly gaining popularity as platforms for collecting and sharing sensor data, such as the accelerometer, gyroscope, and rotation sensor. These sensors are used to improve the convenience of smartphone users, e.g., supporting the mobile UI motion-based commands. Although these motion sensors do not require users’ permissions, they still bring potential risks of leaking users’ private information reflected by the changes of sensor readings. In this paper, we investigate the feasibility of inferring a user’s handwritten pattern on a smartphone touchscreen by using the embedded motion sensors. Specifically, our inference attack is composed of two key steps where we 1) first exploit the dynamic time warping (DTW) technique to differentiate any pair of time-series sensor recordings corresponding to different handwritten patterns; and 2) develop a novel sensor fusion mechanism to integrate information contained in multiple motion sensors by exploiting the majority voting strategy. Through extensive experiments using real-world data sets, we demonstrate the effectiveness of our proposed attack which can achieve 91.4% accuracy for inferring smartphone users’ handwritten patterns.

Paper Citation

in Harvard Style

Lee W., Ortiz J., Ko B. and Lee R. (2018). Inferring Smartphone Users’ Handwritten Patterns by using Motion Sensors.In Proceedings of the 4th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP, ISBN 978-989-758-282-0, pages 139-148. DOI: 10.5220/0006650301390148

in Bibtex Style

@conference{icissp18,
author={Wei-Han Lee and Jorge Ortiz and Bongjun Ko and Ruby Lee},
title={Inferring Smartphone Users’ Handwritten Patterns by using Motion Sensors},
booktitle={Proceedings of the 4th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,},
year={2018},
pages={139-148},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006650301390148},
isbn={978-989-758-282-0},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 4th International Conference on Information Systems Security and Privacy - Volume 1: ICISSP,
TI - Inferring Smartphone Users’ Handwritten Patterns by using Motion Sensors
SN - 978-989-758-282-0
AU - Lee W.
AU - Ortiz J.
AU - Ko B.
AU - Lee R.
PY - 2018
SP - 139
EP - 148
DO - 10.5220/0006650301390148