TKCA: a timely keystroke-based continuous user authentication with short keystroke sequence in uncontrolled settings

Abstract Keystroke-based behavioral biometrics have been proven effective for continuous user authentication. Current state-of-the-art algorithms have achieved outstanding results in long text or short text collected by doing some tasks. It remains a considerable challenge to authenticate users cont...

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Main Authors: Lulu Yang, Chen Li, Ruibang You, Bibo Tu, Linghui Li
Format: Article
Language:English
Published: SpringerOpen 2021-05-01
Series:Cybersecurity
Subjects:
Online Access:https://doi.org/10.1186/s42400-021-00075-9
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spelling doaj-7be928241b3d476a874b4751ac0cd8ac2021-05-09T11:03:33ZengSpringerOpenCybersecurity2523-32462021-05-014111610.1186/s42400-021-00075-9TKCA: a timely keystroke-based continuous user authentication with short keystroke sequence in uncontrolled settingsLulu Yang0Chen Li1Ruibang You2Bibo Tu3Linghui Li4Institute of Information Engineering, Chinese Academy of SciencesInstitute of Information Engineering, Chinese Academy of SciencesInstitute of Information Engineering, Chinese Academy of SciencesInstitute of Information Engineering, Chinese Academy of SciencesKey Laboratory of Trustworthy Distributed Computing and Service, Ministry of Education, Beijing University of Posts and TelecommunicationsAbstract Keystroke-based behavioral biometrics have been proven effective for continuous user authentication. Current state-of-the-art algorithms have achieved outstanding results in long text or short text collected by doing some tasks. It remains a considerable challenge to authenticate users continuously and accurately with short keystroke inputs collected in uncontrolled settings. In this work, we propose a Timely Keystroke-based method for Continuous user Authentication, named TKCA. It integrates the key name and two kinds of timing features through an embedding mechanism. And it captures the relationship between context keystrokes by the Bidirectional Long Short-Term Memory (Bi-LSTM) network. We conduct a series of experiments to validate it on a public dataset - the Clarkson II dataset collected in a completely uncontrolled and natural setting. Experiment results show that the proposed TKCA achieves state-of-the-art performance with 8.28% of EER when using only 30 keystrokes and 2.78% of EER when using 190 keystrokes.https://doi.org/10.1186/s42400-021-00075-9Keystroke dynamicsContinuous user authenticationEmbeddingLSTMBi-LSTM
collection DOAJ
language English
format Article
sources DOAJ
author Lulu Yang
Chen Li
Ruibang You
Bibo Tu
Linghui Li
spellingShingle Lulu Yang
Chen Li
Ruibang You
Bibo Tu
Linghui Li
TKCA: a timely keystroke-based continuous user authentication with short keystroke sequence in uncontrolled settings
Cybersecurity
Keystroke dynamics
Continuous user authentication
Embedding
LSTM
Bi-LSTM
author_facet Lulu Yang
Chen Li
Ruibang You
Bibo Tu
Linghui Li
author_sort Lulu Yang
title TKCA: a timely keystroke-based continuous user authentication with short keystroke sequence in uncontrolled settings
title_short TKCA: a timely keystroke-based continuous user authentication with short keystroke sequence in uncontrolled settings
title_full TKCA: a timely keystroke-based continuous user authentication with short keystroke sequence in uncontrolled settings
title_fullStr TKCA: a timely keystroke-based continuous user authentication with short keystroke sequence in uncontrolled settings
title_full_unstemmed TKCA: a timely keystroke-based continuous user authentication with short keystroke sequence in uncontrolled settings
title_sort tkca: a timely keystroke-based continuous user authentication with short keystroke sequence in uncontrolled settings
publisher SpringerOpen
series Cybersecurity
issn 2523-3246
publishDate 2021-05-01
description Abstract Keystroke-based behavioral biometrics have been proven effective for continuous user authentication. Current state-of-the-art algorithms have achieved outstanding results in long text or short text collected by doing some tasks. It remains a considerable challenge to authenticate users continuously and accurately with short keystroke inputs collected in uncontrolled settings. In this work, we propose a Timely Keystroke-based method for Continuous user Authentication, named TKCA. It integrates the key name and two kinds of timing features through an embedding mechanism. And it captures the relationship between context keystrokes by the Bidirectional Long Short-Term Memory (Bi-LSTM) network. We conduct a series of experiments to validate it on a public dataset - the Clarkson II dataset collected in a completely uncontrolled and natural setting. Experiment results show that the proposed TKCA achieves state-of-the-art performance with 8.28% of EER when using only 30 keystrokes and 2.78% of EER when using 190 keystrokes.
topic Keystroke dynamics
Continuous user authentication
Embedding
LSTM
Bi-LSTM
url https://doi.org/10.1186/s42400-021-00075-9
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