Projection-Based Person Identification

Neubrandt, Dóra; Búza, Krisztián

doi:10.1007/978-3-319-59162-9_23

Advances in Intelligent Systems and Computing

2017

DOI: 10.1007/978-3-319-59162-9_23

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Projection-Based Person Identification

Dóra Neubrandt

Krisztián Búza

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2023

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SapiPin: Observations on PIN-code typing dynamics

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Búza

2023

Acta Universitatis Sapientiae, Informatica

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In this paper, we report on PIN-code typing behaviour on touchscreen devices of 112 subjects. Detailed statistical analysis revealed that the major di erence between subjects is in inter-key latency. Key-press duration variations are insignificant compared to inter-key latency variations. Subjects were grouped into meaningful clusters using clustering. The resulting clusters were of slow, medium, and fast typists. The dataset was split randomly into two equal size subsets. The first subset was used to train different synthetic data generators, while the second subset was used to evaluate an authentication attack using the generated synthetic data. The evaluation showed that slow typists were the hardest to attack. Both the dataset and the software are publicly available at https://github.com/margitantal68/sapipin_paper.

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SapiPin: Observations on PIN-code typing dynamics

Antal

Búza

2023

Acta Universitatis Sapientiae, Informatica

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scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.

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Projection-Based Person Identification

Cited by 1 publication

References 14 publications

SapiPin: Observations on PIN-code typing dynamics

SapiPin: Observations on PIN-code typing dynamics

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