Inferring smartphone users’ handwritten patterns by using motion sensors

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

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Scopus citations

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.

Original languageEnglish (US)
Title of host publicationICISSP 2018 - Proceedings of the 4th International Conference on Information Systems Security and Privacy
EditorsPaolo Mori, Steven Furnell, Olivier Camp
PublisherSciTePress
Pages139-148
Number of pages10
ISBN (Electronic)9789897582820
DOIs
StatePublished - 2018
Event4th International Conference on Information Systems Security and Privacy, ICISSP 2018 - Funchal, Madeira, Portugal
Duration: Jan 22 2018Jan 24 2018

Publication series

NameICISSP 2018 - Proceedings of the 4th International Conference on Information Systems Security and Privacy
Volume2018-January

Other

Other4th International Conference on Information Systems Security and Privacy, ICISSP 2018
CountryPortugal
CityFunchal, Madeira
Period1/22/181/24/18

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Information Systems
  • Computer Networks and Communications
  • Safety, Risk, Reliability and Quality

Keywords

  • Dynamic Timing Warping
  • Handwritten Pattern
  • Majority Voting
  • Smartphone Sensors

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  • Cite this

    Lee, W. H., Ortiz, J., Ko, B., & Lee, R. (2018). Inferring smartphone users’ handwritten patterns by using motion sensors. In P. Mori, S. Furnell, & O. Camp (Eds.), ICISSP 2018 - Proceedings of the 4th International Conference on Information Systems Security and Privacy (pp. 139-148). (ICISSP 2018 - Proceedings of the 4th International Conference on Information Systems Security and Privacy; Vol. 2018-January). SciTePress. https://doi.org/10.5220/0006650301390148