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Using mobile device screens for authentication

Published: 28 November 2011 Publication History

Abstract

Authentication in public spaces, such as ATM PIN entry, is inherently susceptible to security attacks based on observation in person or via cameras. This paper addresses this problem with a system which allows users to enter a PIN on a standard mobile phone and then transmit it securely for authentication using modulated patterns of light shown on the screen and sensed by a cheap bespoke receiver unit. No pre-pairing is required as physical proximity guarantees security. The paper presents several hardware and software variations, evaluates the technical soundness of the system, and presents two user studies addressing usability and security against observation attacks.

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Cited By

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  • (2021)Prototyping Usable Privacy and Security Systems: Insights from ExpertsInternational Journal of Human–Computer Interaction10.1080/10447318.2021.1949134(1-23)Online publication date: 5-Aug-2021
  • (2021)A Behaviour‐Based Authentication to Internet of Things Using Machine LearningDesign and Development of Efficient Energy Systems10.1002/9781119761785.ch14(245-263)Online publication date: 15-Apr-2021
  • (2018)A Survey of Machine Learning Techniques for Behavioral-Based Biometric User AuthenticationRecent Advances in Cryptography and Network Security10.5772/intechopen.76685Online publication date: 31-Oct-2018
  • Show More Cited By

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    cover image ACM Other conferences
    OzCHI '11: Proceedings of the 23rd Australian Computer-Human Interaction Conference
    November 2011
    363 pages
    ISBN:9781450310901
    DOI:10.1145/2071536
    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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    • Human Factors & Ergonomics Soc: Human Factors & Ergonomics Soc

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    Association for Computing Machinery

    New York, NY, United States

    Publication History

    Published: 28 November 2011

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    Author Tags

    1. PIN entry
    2. authentication
    3. light
    4. mobile interface

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    • Research-article

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    OzCHI '11
    Sponsor:
    • Human Factors & Ergonomics Soc

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    Overall Acceptance Rate 362 of 729 submissions, 50%

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    Cited By

    View all
    • (2021)Prototyping Usable Privacy and Security Systems: Insights from ExpertsInternational Journal of Human–Computer Interaction10.1080/10447318.2021.1949134(1-23)Online publication date: 5-Aug-2021
    • (2021)A Behaviour‐Based Authentication to Internet of Things Using Machine LearningDesign and Development of Efficient Energy Systems10.1002/9781119761785.ch14(245-263)Online publication date: 15-Apr-2021
    • (2018)A Survey of Machine Learning Techniques for Behavioral-Based Biometric User AuthenticationRecent Advances in Cryptography and Network Security10.5772/intechopen.76685Online publication date: 31-Oct-2018
    • (2015)Authentication MeleeProceedings of the 24th International Conference on World Wide Web10.1145/2736277.2741683(916-926)Online publication date: 18-May-2015
    • (2015)Exploiting Ambient Light Sensor for Authentication on Wearable Devices2015 Fourth International Conference on Cyber Security, Cyber Warfare, and Digital Forensic (CyberSec)10.1109/CyberSec.2015.27(95-100)Online publication date: Oct-2015
    • (2012)Don't queue up!Proceedings of the 11th International Conference on Mobile and Ubiquitous Multimedia10.1145/2406367.2406422(1-4)Online publication date: 4-Dec-2012
    • (2012)Counting clicks and beepsInteracting with Computers10.1016/j.intcom.2012.06.00524:5(409-422)Online publication date: 1-Sep-2012

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