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Challenge-response behavioral mobile authentication: a comparative study of graphical patterns and cognitive games

Published: 09 December 2019 Publication History

Abstract

The most researched behavioral biometrics for mobile device authentication involves the use of touch gestures as the user enters a graphical pattern password (like the one used on Android) or otherwise interacts with the device. However, due to the inherent static nature of these schemes, they are vulnerable to impersonation attacks. In this paper, we investigate challenge-response mechanisms to address this security vulnerability underlying the traditional static biometric schemes. We study the performance, security, and usability of two schemes of such challenge-response interactive biometric authentication geared for mobile devices and contrast them to static graphical pattern based biometrics. The first scheme is based on random graphical patterns. The second scheme, recently introduced for PC class of devices (not mobile), is based on a simple cognitive game involving semantic interactive random challenges. Our results show that the accuracy of user identification with these approaches is similar to static pattern based biometric scheme. Finally, we argue that utilizing interactivity and randomization significantly enhance the security against impersonation attacks. As an independent result, our work demonstrates that the use of motion sensors available on mobile device serves to improve the identification accuracy of schemes that only use touch-based gestures (static and interactive).

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Cited By

View all
  • (2023)Methods to Encrypt and Authenticate Digital Files in Distributed Networks and Zero-Trust EnvironmentsAxioms10.3390/axioms1206053112:6(531)Online publication date: 29-May-2023
  • (2022)PCR-Auth: Solving Authentication Puzzle Challenge with Encoded Palm Contact Response2022 IEEE Symposium on Security and Privacy (SP)10.1109/SP46214.2022.9833564(1034-1048)Online publication date: May-2022
  • (2021)Adversary Models for Mobile Device AuthenticationACM Computing Surveys10.1145/347760154:9(1-35)Online publication date: 8-Oct-2021

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    cover image ACM Other conferences
    ACSAC '19: Proceedings of the 35th Annual Computer Security Applications Conference
    December 2019
    821 pages
    ISBN:9781450376280
    DOI:10.1145/3359789
    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 ACM 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: 09 December 2019

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    Author Tags

    1. behavioral authentication
    2. cognitive games
    3. graphical patterns
    4. mobile authentication

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    ACSAC '19
    ACSAC '19: 2019 Annual Computer Security Applications Conference
    December 9 - 13, 2019
    Puerto Rico, San Juan, USA

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    ACSAC '19 Paper Acceptance Rate 60 of 266 submissions, 23%;
    Overall Acceptance Rate 104 of 497 submissions, 21%

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    Cited By

    View all
    • (2023)Methods to Encrypt and Authenticate Digital Files in Distributed Networks and Zero-Trust EnvironmentsAxioms10.3390/axioms1206053112:6(531)Online publication date: 29-May-2023
    • (2022)PCR-Auth: Solving Authentication Puzzle Challenge with Encoded Palm Contact Response2022 IEEE Symposium on Security and Privacy (SP)10.1109/SP46214.2022.9833564(1034-1048)Online publication date: May-2022
    • (2021)Adversary Models for Mobile Device AuthenticationACM Computing Surveys10.1145/347760154:9(1-35)Online publication date: 8-Oct-2021

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