Feature Subset for Improving Accuracy of Keystroke Dynamics on Mobile Environment


Sung-Hoon Lee, Jong-hyuk Roh, SooHyung Kim, Seung-Hun Jin, Journal of Information Processing Systems
Vol. 14, No. 2, pp. 523-538, Apr. 2018
10.3745/JIPS.03.0093
Keywords: Feature Subset, Keystroke Dynamics, Smartphone Sensor
Fulltext:

Abstract

Keystroke dynamics user authentication is a behavior-based authentication method which analyzes patterns in how a user enters passwords and PINs to authenticate the user. Even if a password or PIN is revealed to another user, it analyzes the input pattern to authenticate the user; hence, it can compensate for the drawbacks of knowledge-based (what you know) authentication. However, users' input patterns are not always fixed, and each user's touch method is different. Therefore, there are limitations to extracting the same features for all users to create a user's pattern and perform authentication. In this study, we perform experiments to examine the changes in user authentication performance when using feature vectors customized for each user versus using all features. User customized features show a mean improvement of over 6% in error equal rate, as compared to when all features are used.


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Cite this article
[APA Style]
Sung-Hoon Lee, Jong-hyuk Roh, SooHyung Kim, & Seung-Hun Jin (2018). Feature Subset for Improving Accuracy of Keystroke Dynamics on Mobile Environment. Journal of Information Processing Systems, 14(2), 523-538. DOI: 10.3745/JIPS.03.0093.

[IEEE Style]
S. Lee, J. Roh, S. Kim and S. Jin, "Feature Subset for Improving Accuracy of Keystroke Dynamics on Mobile Environment," Journal of Information Processing Systems, vol. 14, no. 2, pp. 523-538, 2018. DOI: 10.3745/JIPS.03.0093.

[ACM Style]
Sung-Hoon Lee, Jong-hyuk Roh, SooHyung Kim, and Seung-Hun Jin. 2018. Feature Subset for Improving Accuracy of Keystroke Dynamics on Mobile Environment. Journal of Information Processing Systems, 14, 2, (2018), 523-538. DOI: 10.3745/JIPS.03.0093.