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Security and Communication Networks
Volume 2018, Article ID 2567463, 10 pages
Research Article

Understanding Keystroke Dynamics for Smartphone Users Authentication and Keystroke Dynamics on Smartphones Built-In Motion Sensors

1Department of Computer and Information Security, Sejong University, Seoul 05006, Republic of Korea
2Electronics and Telecommunications Research Institute, Daejeon 34113, Republic of Korea
3Information Security Engineering, University of Science and Technology, Daejeon 34113, Republic of Korea

Correspondence should be addressed to Ji Sun Shin; moc.liamg@gnojes.nihssj

Received 3 November 2017; Revised 19 January 2018; Accepted 13 February 2018; Published 14 March 2018

Academic Editor: Amir Anees

Copyright © 2018 Hyungu Lee et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Personal Identification Numbers (PINs) and pattern drawing have been used as common authentication methods especially on smartphones. Such methods, however, are very vulnerable to the shoulder surfing attack. Thus, keystroke dynamics that authenticate legitimate users based on their typing manner have been studied for years. However, many of the studies have focused on PC keyboard keystrokes. More studies on mobile and smartphones keystroke dynamics are warranted; as smartphones make progress in both hardware and software, features from smartphones have been diversified. In this paper, using various features including keystroke data such as time interval and motion data such as accelerometers and rotation values, we evaluate features with motion data and without motion data. We also compare 5 formulas for motion data, respectively. We also demonstrate that opposite gender match between a legitimate user and impostors has influence on authenticating by our experiment results.