Authors:
Sandeep Gupta
1
;
2
;
Rajesh Kumar
3
;
Kiran Raja
4
;
Bruno Crispo
1
and
Carsten Maple
5
Affiliations:
1
Department of Information Engineering & Computer Science (DISI), University of Trento, Italy
;
2
Centre for Secure Information Technologies (CSIT), Queen’s University Belfast, U.K.
;
3
Bucknell University, U.S.A.
;
4
Norwegian University of Science and Technology (NTNU), Norway
;
5
Secure Cyber Systems Research Group (SCSRG), Warwick Manufacturing Group (WMG), University of Warwick, Coventry, U.K.
Keyword(s):
Smartphones, Biometrics, User Verification, Synthetic Data, Robustness.
Abstract:
Smartphones balance security and convenience by offering both knowledge-based (PINs, patterns) and biometric (facial, fingerprint) verification methods. However, studies have reported that PINs and patterns can be readily circumvented, while synthetically manipulated face data can easily deceive smartphone facial verification mechanisms. In this paper, we design a bimodal user verification mechanism that combines behavioral (pickup gesture) and biological (face) biometrics for user verification on smartphones. This work establishes a baseline for single-user verification scenarios on smartphones using a one-class verification model. The evaluation is performed in two stages: first, performance is assessed in both unimodal and bimodal settings using publicly available datasets; second, the robustness of the employed biological and behavioral traits is examined against four diverse attacks. Our findings emphasize the necessity of investigating diverse attack vectors, particularly fully
synthetic data, to design robust user verification mechanisms.
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