TY - GEN
T1 - Global Feature Analysis and Comparative Evaluation of Freestyle In-Air-Handwriting Passcode for User Authentication
AU - Lu, Duo
AU - Deng, Yuli
AU - Huang, Dijiang
N1 - Publisher Copyright:
© 2021 Association for Computing Machinery.
PY - 2021/12/6
Y1 - 2021/12/6
N2 - Freestyle in-air-handwriting passcode-based user authentication methods address the needs for Virtual Reality (VR)/Augmented Reality (AR) headsets, wearable devices, and game consoles where a physical keyboard cannot be provided for typing a password, but a gesture input interface is readily available. Such an authentication system can capture the hand movement of writing a passcode string in the air and verify the user identity using both the writing content (like a password) and the writing style (like a behavior biometric trait). However, distinguishing handwriting signals from different users is challenging in signal processing, feature extraction, and matching. In this paper, we provide a detailed analysis of the global features of in-air-handwriting signals and a comparative evaluation of such a user authentication framework. Also, we build a prototype system with two different types of hand motion capture devices, collect two datasets, and conduct an extensive evaluation.
AB - Freestyle in-air-handwriting passcode-based user authentication methods address the needs for Virtual Reality (VR)/Augmented Reality (AR) headsets, wearable devices, and game consoles where a physical keyboard cannot be provided for typing a password, but a gesture input interface is readily available. Such an authentication system can capture the hand movement of writing a passcode string in the air and verify the user identity using both the writing content (like a password) and the writing style (like a behavior biometric trait). However, distinguishing handwriting signals from different users is challenging in signal processing, feature extraction, and matching. In this paper, we provide a detailed analysis of the global features of in-air-handwriting signals and a comparative evaluation of such a user authentication framework. Also, we build a prototype system with two different types of hand motion capture devices, collect two datasets, and conduct an extensive evaluation.
KW - Gesture input interface
KW - In-air-handwriting
KW - User authentication
UR - http://www.scopus.com/inward/record.url?scp=85121636746&partnerID=8YFLogxK
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U2 - 10.1145/3485832.3485906
DO - 10.1145/3485832.3485906
M3 - Conference contribution
AN - SCOPUS:85121636746
T3 - ACM International Conference Proceeding Series
SP - 468
EP - 481
BT - Proceedings - 37th Annual Computer Security Applications Conference, ACSAC 2021
PB - Association for Computing Machinery
T2 - 37th Annual Computer Security Applications Conference, ACSAC 2021
Y2 - 6 December 2021 through 10 December 2021
ER -