BioTouchPass: Handwritten Passwords for Touchscreen Biometrics
Entity
UAM. Departamento de Tecnología Electrónica y de las ComunicacionesPublisher
IEEEDate
2020Citation
10.1109/TMC.2019.2911506
IEEE Transactions on Mobile Computing 19.7 (2020): 1532-1543
ISSN
1536-1233 (print); 1558-0660 (online)DOI
10.1109/TMC.2019.2911506Funded by
This work has been supported by projects: BIBECA (MINECO), Bio-Guard (Ayudas Fundación BBVA a Equipos de Investigación Científica 2017) and by UAM-CecaBank. Ruben Tolosana is supported by a FPU Fellowship from Spanish MECDProject
Gobierno de España. RTI2018- 101248-B-I00Editor's Version
https://doi.org/10.1109/TMC.2019.2911506Subjects
Biometrics; Passwords; PIN; OTP; Handwriting; TelecomunicacionesNote
This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibleRights
© IEEEAbstract
This work enhances traditional authentication systems based on Personal Identification Numbers (PIN) and One-
Time Passwords (OTP) through the incorporation of biometric information as a second level of user authentication. In our
proposed approach, users draw each digit of the password on the touchscreen of the device instead of typing them as usual. A
complete analysis of our proposed biometric system is carried out regarding the discriminative power of each handwritten digit and
the robustness when increasing the length of the password and the number of enrolment samples. The new e-BioDigit database,
which comprises on-line handwritten digits from 0 to 9, has been acquired using the finger as input on a mobile device. This
database is used in the experiments reported in this work and it is available together with benchmark results in GitHub1. Finally,
we discuss specific details for the deployment of our proposed approach on current PIN and OTP systems, achieving results with
Equal Error Rates (EERs) ca. 4.0% when the attacker knows the password. These results encourage the deployment of our
proposed approach in comparison to traditional PIN and OTP systems where the attack would have 100% success rate under
the same impostor scenario
Files in this item
Google Scholar:Tolosana Moranchel, Rubén
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Vera Rodríguez, Rubén
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Fiérrez Aguilar, Julián
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