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SWIPEGAN: Swiping Data Augmentation Using Generative Adversarial Networks for Smartphone User Authentication

Published: 28 June 2021 Publication History

Abstract

Behavioral biometric-based smartphone user authentication schemes based on touch/swipe have shown to provide the desired usability. However, their accuracy is not yet considered up to the mark. This is primarily due to the lack of a sufficient number of training samples, e.g., swiping gestures1: users are reluctant to provide many. Consequently, the application of such authentication techniques in the real world is still limited.
To overcome the shortage of training samples and make behavioral biometric-based schemes more accurate, we propose the usage of Generative Adversarial Networks (GAN) for generating synthetic samples, in our case, or swiping gestures. GAN is an unsupervised approach for synthetic data generation and has already been used in a wide range of applications, such as image and video generation. However, their use in behavioral biometric-based user authentication schemes has not been explored yet. In this paper, we propose SWIPEGAN - to generate swiping samples to be used for smartphone user authentication. Extensive experimentation and evaluation show the quality of the generated synthetic swiping samples and their efficacy in increasing the accuracy of the authentication scheme.

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  • (2024)CoreTemp: Coreset Sampled Templates for Multimodal Mobile BiometricsApplied Sciences10.3390/app1412518314:12(5183)Online publication date: 14-Jun-2024
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  1. SWIPEGAN: Swiping Data Augmentation Using Generative Adversarial Networks for Smartphone User Authentication

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    cover image ACM Conferences
    WiseML '21: Proceedings of the 3rd ACM Workshop on Wireless Security and Machine Learning
    June 2021
    104 pages
    ISBN:9781450385619
    DOI:10.1145/3468218
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    Published: 28 June 2021

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    Author Tags

    1. Behavioral Authentication
    2. Generative Networks
    3. Smartphone

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    Cited By

    View all
    • (2024)CoreTemp: Coreset Sampled Templates for Multimodal Mobile BiometricsApplied Sciences10.3390/app1412518314:12(5183)Online publication date: 14-Jun-2024
    • (2024)Towards a Framework for Evaluating Synthetic Surface GesturesCompanion Proceedings of the 16th ACM SIGCHI Symposium on Engineering Interactive Computing Systems10.1145/3660515.3661327(22-30)Online publication date: 24-Jun-2024
    • (2024)Touch-Based Continuous Mobile Device Authentication Using One-vs-One Classification Approach2024 IEEE International Conference on Big Data and Smart Computing (BigComp)10.1109/BigComp60711.2024.00034(167-174)Online publication date: 18-Feb-2024
    • (2024)Wearable Wisdom: A Bi-Modal Behavioral Biometric Scheme for Smartwatch User AuthenticationIEEE Access10.1109/ACCESS.2024.339512812(61221-61234)Online publication date: 2024
    • (2023)Synthesis of 3D on-air signatures with the Sigma–Lognormal modelKnowledge-Based Systems10.1016/j.knosys.2023.110365265:COnline publication date: 8-Apr-2023
    • (2023)Swipe gestures for user authentication in smartphonesJournal of Information Security and Applications10.1016/j.jisa.2023.10345074:COnline publication date: 1-May-2023
    • (2022)Few-Shot Continuous Authentication for Mobile-Based BiometricsApplied Sciences10.3390/app12201036512:20(10365)Online publication date: 14-Oct-2022

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