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Pulse-Response: Exploring Human Body Impedance for Biometric Recognition

Published: 25 May 2017 Publication History

Abstract

Biometric characteristics are often used as a supplementary component in user authentication and identification schemes. Many biometric traits, both physiological and behavioral, offering a wider range of security and stability, have been explored. We propose a new physiological trait based on the human body’s electrical response to a square pulse signal, called pulse-response, and analyze how this biometric characteristic can be used to enhance security in the context of two example applications: (1) an additional authentication mechanism in PIN entry systems and (2) a means of continuous authentication on a secure terminal. The pulse-response biometric recognition is effective because each human body exhibits a unique response to a signal pulse applied at the palm of one hand and measured at the palm of the other. This identification mechanism integrates well with other established methods and could offer an additional layer of security, either on a continuous basis or at log-in time. We build a proof-of-concept prototype and perform experiments to assess the feasibility of pulse-response for biometric authentication. The results are very encouraging, achieving an equal error rate of 2% over a static dataset and 9% over a dataset with samples taken over several weeks. We also quantize resistance to attack by estimating individual worst-case probabilities for zero-effort impersonation in different experiments.

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        cover image ACM Transactions on Privacy and Security
        ACM Transactions on Privacy and Security  Volume 20, Issue 2
        May 2017
        87 pages
        ISSN:2471-2566
        EISSN:2471-2574
        DOI:10.1145/3064808
        Issue’s Table of Contents
        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: 25 May 2017
        Accepted: 01 March 2017
        Revised: 01 July 2016
        Received: 01 January 2016
        Published in TOPS Volume 20, Issue 2

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        Author Tags

        1. Biometric authentication
        2. biometric recognition
        3. biometrics
        4. continuous authentication
        5. physiological trait
        6. secure PIN entry
        7. secure computer terminal
        8. secure man--machine interaction
        9. user identification

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        • (2024)Exploring a Secure Device Pairing Using Human Body as a ConductorIEEE Transactions on Mobile Computing10.1109/TMC.2024.340601623:12(12097-12112)Online publication date: 1-Dec-2024
        • (2023)uKnit: A Position-Aware Reconfigurable Machine-Knitted Wearable for Gestural Interaction and Passive Sensing using Electrical Impedance TomographyProceedings of the 2023 CHI Conference on Human Factors in Computing Systems10.1145/3544548.3580692(1-17)Online publication date: 19-Apr-2023
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        • (2022)Enabling secure touch-to-access device pairing based on human body's electrical responseProceedings of the 28th Annual International Conference on Mobile Computing And Networking10.1145/3495243.3564146(556-569)Online publication date: 14-Oct-2022
        • (2022)A Fingertip Profiled RF IdentifierIEEE Transactions on Mobile Computing10.1109/TMC.2020.301409221:2(392-407)Online publication date: 1-Feb-2022
        • (2019)Biometric Recognition Using Multimodal Physiological SignalsIEEE Access10.1109/ACCESS.2019.29238567(83581-83588)Online publication date: 2019
        • (2018)Bionyms: Driver-centric Message Authentication using Biometric Measurements2018 IEEE Vehicular Networking Conference (VNC)10.1109/VNC.2018.8628359(1-8)Online publication date: Dec-2018

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