A Human Factors Study of Graphical Passwords Using Biometrics
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One mode of authentication used in modern computing systems is graphical passwords. Graphical passwords are becoming more popular because touch-sensitive and pen-sensitive technologies are becoming ubiquitous. In this paper, we construct the “BioSketch” database, which is a general database of sketch-based passwords (SkPWs) with pressure information used as a biometric property. The BioSketch database is created so that recognition approaches may be commensurable with the benchmark performances. Using this database, we are also able to study the human-computer interaction (HCI) process for SkPWs. In this paper, we compare a generalized SKS recognition algorithm with the Fréchet distance in terms of the intra/inter-class variations and performances. The results show that the SKS-based approach achieves as much as a 7 % and 17 % reduction in equal error rate (EER) for random and skilled forgeries respectively.
KeywordsDynamic Time Warping Equal Error Rate False Acceptance Rate False Rejection Rate Benchmark Performance
The information in this paper is based on work partially funded by the United States Army Research Office (ARO) grant W911NF-04-D-0003-0019.
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