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When kids' toys breach mobile phone security

Published: 04 November 2013 Publication History

Abstract

Touch-based verification --- the use of touch gestures (e.g., swiping, zooming, etc.) to authenticate users of touch screen devices --- has recently been widely evaluated for its potential to serve as a second layer of defense to the PIN lock mechanism. In all performance evaluations of touch-based authentication systems however, researchers have assumed naive (zero-effort) forgeries in which the attacker makes no effort to mimic a given gesture pattern.
In this paper we demonstrate that a simple "Lego" robot driven by input gleaned from general population swiping statistics can generate forgeries that achieve alarmingly high penetration rates against touch-based authentication systems. Using the best classification algorithms in touch-based authentication, we rigorously explore the effect of the attack, finding that it increases the Equal Error Rates of the classifiers by between 339% and 1004% depending on parameters such as the failure-to-enroll threshold and the type of touch stroke generated by the robot. The paper calls into question the zero-effort impostor testing approach used to benchmark the performance of touch-based authentication systems.

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    cover image ACM Conferences
    CCS '13: Proceedings of the 2013 ACM SIGSAC conference on Computer & communications security
    November 2013
    1530 pages
    ISBN:9781450324779
    DOI:10.1145/2508859
    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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    Published: 04 November 2013

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    Author Tags

    1. attack
    2. authentication
    3. biometrics
    4. robot
    5. touch gestures

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