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

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 ha...

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Bibliographic Details
Published in:Security and communication networks 2018-01, Vol.2018 (2018), p.1-10
Main Authors: Lee, Sung-Hoon, Lee, Shincheol, Kim, Dong In, Hwang, Jung Yeon, Lee, Hyungu, Shin, Ji Sun
Format: Article
Language:English
Subjects:
Accelerometers
Accuracy
Biometrics
Classification
Dynamics
Experiments
Gender
Interactive computer systems
Keyboards
Motion sensors
Neural networks
Personal computers
Personal identification numbers
Sensors
Smartphones
Surfing
Usability
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Summary: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.
ISSN:1939-0114
1939-0122
DOI:10.1155/2018/2567463