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A User Study of Keystroke Dynamics as Second Factor in Web MFA

Published: 24 April 2023 Publication History

Abstract

As account compromises and malicious online attacks are on the rise, multi-factor authentication (MFA) has been adopted to defend against these attacks. OTP and mobile push notification are just two examples of the popularly adopted MFA factors. Although MFA improve security, they also add additional steps or hardware to the authentication process, thus increasing the authentication time and introducing friction. On the other hand, keystroke dynamics-based authentication is believed to be a promising MFA for increasing security while reducing friction. While there have been several studies on the usability of other MFA factors, the usability of keystroke dynamics has not been studied. To this end, we have built a web authentication system with the standard features of signup, login and account recovery, and integrated keystroke dynamics as an additional factor. We then conducted a user study on the system where 20 participants completed tasks related to signup, login and account recovery. We have also evaluated a new approach for completing the user enrollment process, which reduces friction by naturally employing other alternative MFA factors (OTP in our study) when keystroke dynamics is not ready for use. Our study shows that while maintaining strong security (0% FPR), adding keystroke dynamics reduces authentication friction by avoiding 66.3% of OTP at login and 85.8% of OTP at account recovery, which in turn reduces the authentication time by 63.3% and 78.9% for login and account recovery respectively. Through an exit survey, all participants have rated the integration of keystroke dynamics with OTP to be more preferable to the conventional OTP-only authentication.

Supplemental Material

MP4 File
We conducted a web-based user study of keystroke dynamics-based authentication where keystroke dynamics was integrated with OTP to improve usability and reduce friction while maintaining security. Using a standard consumer website that we built for this study, participants completed tasks related to signup, login and account recovery. We also implemented a new enrollment process approach for building the user?s profile without introducing enrollment friction. The OTP-based auth was used as the initial auth factor until the enrollment process is complete, and subsequent login or account recovery attempts uses the keystroke dynamics-based auth factor. We analysed the usability of keystroke dynamics-based auth using the following measures: authentication time, security, convenience and participants feedback. Overall, our study shows that while maintaining strong security, adding keystroke dynamics-based authentication significantly reduces authentication friction, leading to reduction in authentication time.

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Cited By

View all
  • (2024)Mouse Dynamics Behavioral Biometrics: A SurveyACM Computing Surveys10.1145/364031156:6(1-33)Online publication date: 24-Jan-2024
  • (2023)Siamese Neural Network for Keystroke Dynamics-Based Authentication on Partial PasswordsSensors10.3390/s2315668523:15(6685)Online publication date: 26-Jul-2023
  • (2023)Impact of Data Breadth and Depth on Performance of Siamese Neural Network Model: Experiments with Two Behavioral Biometric Datasets2023 International Conference of the Biometrics Special Interest Group (BIOSIG)10.1109/BIOSIG58226.2023.10345993(1-6)Online publication date: 20-Sep-2023

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    cover image ACM Conferences
    CODASPY '23: Proceedings of the Thirteenth ACM Conference on Data and Application Security and Privacy
    April 2023
    304 pages
    ISBN:9798400700675
    DOI:10.1145/3577923
    Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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    Publication History

    Published: 24 April 2023

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    Author Tags

    1. keystroke dynamics
    2. multi-factor authentication
    3. two-factor authentication
    4. usability
    5. user study
    6. web

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    • Research-article

    Data Availability

    We conducted a web-based user study of keystroke dynamics-based authentication where keystroke dynamics was integrated with OTP to improve usability and reduce friction while maintaining security. Using a standard consumer website that we built for this study, participants completed tasks related to signup, login and account recovery. We also implemented a new enrollment process approach for building the user?s profile without introducing enrollment friction. The OTP-based auth was used as the initial auth factor until the enrollment process is complete, and subsequent login or account recovery attempts uses the keystroke dynamics-based auth factor. We analysed the usability of keystroke dynamics-based auth using the following measures: authentication time, security, convenience and participants feedback. Overall, our study shows that while maintaining strong security, adding keystroke dynamics-based authentication significantly reduces authentication friction, leading to reduction in authentication time. https://dl.acm.org/doi/10.1145/3577923.3583642#coda058.mp4

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    • NSF (National Science Foundation)

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    Overall Acceptance Rate 149 of 789 submissions, 19%

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    Cited By

    View all
    • (2024)Mouse Dynamics Behavioral Biometrics: A SurveyACM Computing Surveys10.1145/364031156:6(1-33)Online publication date: 24-Jan-2024
    • (2023)Siamese Neural Network for Keystroke Dynamics-Based Authentication on Partial PasswordsSensors10.3390/s2315668523:15(6685)Online publication date: 26-Jul-2023
    • (2023)Impact of Data Breadth and Depth on Performance of Siamese Neural Network Model: Experiments with Two Behavioral Biometric Datasets2023 International Conference of the Biometrics Special Interest Group (BIOSIG)10.1109/BIOSIG58226.2023.10345993(1-6)Online publication date: 20-Sep-2023

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