Keystroke Dynamics Extraction by Independent Component Analysis and Bio-matrix for User Authentication

Keystroke dynamics is unique specific characteristics used for user authentication problem. There are many researches to detect personal keystroke dynamics and authenticate user based on these characteristics. Most researches study on either the key press durations and multiple key latencies (typing...

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Published inPRICAI 2010: Trends in Artificial Intelligence pp. 477 - 486
Main Authors Nguyen, Thanh Tran, Le, Thai Hoang, Le, Bac Hoai
Format Book Chapter
LanguageEnglish
Published Berlin, Heidelberg Springer Berlin Heidelberg
SeriesLecture Notes in Computer Science
Subjects
Face Recognition
Feature Vector
Independent Component Analysis
User Authentication
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Abstract Keystroke dynamics is unique specific characteristics used for user authentication problem. There are many researches to detect personal keystroke dynamics and authenticate user based on these characteristics. Most researches study on either the key press durations and multiple key latencies (typing time) or key-pressed forces (pressure-based typing) to find the owned personal motif (unique specific characteristic). This paper approaches to extract keystroke dynamics by using independent component analysis (ICA) through a standardized bio-matrix from typing sound signals which contain both typing time and typing force information. The ICA representation of keystroke dynamics is effective for authenticating user in our experiments. The experimental results show that the proposed keystroke dynamics extraction solution is feasible and reliable to solve user authentication problem with false acceptance rate (FAR) 4.12% and false rejection rate (FRR) 5.55%.
AbstractList Keystroke dynamics is unique specific characteristics used for user authentication problem. There are many researches to detect personal keystroke dynamics and authenticate user based on these characteristics. Most researches study on either the key press durations and multiple key latencies (typing time) or key-pressed forces (pressure-based typing) to find the owned personal motif (unique specific characteristic). This paper approaches to extract keystroke dynamics by using independent component analysis (ICA) through a standardized bio-matrix from typing sound signals which contain both typing time and typing force information. The ICA representation of keystroke dynamics is effective for authenticating user in our experiments. The experimental results show that the proposed keystroke dynamics extraction solution is feasible and reliable to solve user authentication problem with false acceptance rate (FAR) 4.12% and false rejection rate (FRR) 5.55%.
Author Le, Thai Hoang
Le, Bac Hoai
Nguyen, Thanh Tran
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Copyright Springer-Verlag Berlin Heidelberg 2010
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DOI 10.1007/978-3-642-15246-7_44
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Snippet Keystroke dynamics is unique specific characteristics used for user authentication problem. There are many researches to detect personal keystroke dynamics and...
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StartPage 477
SubjectTerms Face Recognition
Feature Vector
Independent Component Analysis
User Authentication
Title Keystroke Dynamics Extraction by Independent Component Analysis and Bio-matrix for User Authentication
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