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Journal Article
Understanding Keystroke Dynamics for Smartphone Users Authentication and Keystroke Dynamics on Smartphones Built-In Motion Sensors
- Authors
- Hyungu Lee, Jung Yeon Hwang, Dong In Kim, Shincheol Lee, Sung-Hoon Lee, Ji Sun Shin
- Issue Date
- 2018-03
- Citation
- Security and Communication Networks, v.2018, pp.1-11
- ISSN
- 1939-0114
- Publisher
- Wiley-Blackwell
- Language
- English
- Type
- Journal Article
- Abstract
- 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.
- KSP Keywords
- Authentication method, Built-in, Experiment results, Keystroke Dynamics, Motion Data, Motion sensor, Pc keyboard, Personal identification number, Time interval, hardware and software, shoulder surfing attack
This work is distributed under the term of Creative Commons License (CCL)
(CC BY)
(CC BY)
