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학술지 Feature Subset for Improving Accuracy of Keystroke Dynamics on Mobile Environment
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저자
이성훈, 노종혁, 김수형, 진승헌
발행일
201804
출처
Journal of Information Processing Systems, v.14 no.2, pp.523-538
ISSN
1976-913X
출판사
한국정보처리학회 (KIPS)
DOI
https://dx.doi.org/10.3745/JIPS.03.0093
협약과제
18HH3500, 비대면 본인확인을 위한 바이오 공개키 기반구조 기술 개발, 조상래
초록
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.
KSP 제안 키워드
Authentication method, Feature Vector, Feature subset, Improving accuracy, Input pattern, Keystroke Dynamics, Knowledge-based, User Authentication, behavior-based authentication, mobile environment