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Bimodal Keystroke Dynamics-Based Authentication for Mobile Application Using Anagram

Jurnal Ilmu Komputer dan Informasi (JIKI) · Vol. 15 No. 2 (2022) · pp. 81–91

DOI
10.21609/jiki.v15i2.1015
ISSN
2502-9274, 2088-7051
Published
2022-07-02
Publisher
Faculty of Computer Science - Universitas Indonesia
Language
eng

Abstract

Currently, most of the smartphones recognize uses based on static biometrics, such as face and fingerprint. However, those traits were vulnerable against spoofing attack. For overcoming this problem, dynamic biometrics like the keystroke and gaze are introduced since it is more resistant against spoofing attack. This research focuses on keystroke dynamics for strengthening the user recognition system against spoofing attacks. For recognizing a user, the user keystrokes feature used in the login process is compared with keystroke features stored in the keystroke features database. For evaluating the accuracy of the proposed system, words generated based on the Indonesian anagram are used. Furthermore, for conducting the experiment, 34 participants were asked to type a set of words using the smartphone keyboard. Then, each user’s keystroke is recorded. The keystroke dynamic feature consists of latency and digraph which are extracted from the record. According to the experiment result, the error of the proposed method is decreased by 23.075% of EER with FAR and FRR are decreased by 16.381% and 10.41% respectively, compared with Kim’s method. It means that the proposed method is successful increase the biometrics performance by reducing the error rates

Keywords

Collaboration network of the authors

7 authors · 6 co-authorship links · 1 across different organisations

Hover or tap a name to highlight its co-authors. Double-click to open the author's page.

  • Telkom University
  • Universitas PGRI Kalimantan
  • Different organisations
  • Same organisation
  • Affiliation unknown
  • Thicker line = more joint articles · bigger circle = more articles
Show as table
Co-authorOrganisationJoint articles
Hasmawati HasmawatiTelkom University1
Farah AfiantiTelkom University1
Widhian BramantyaTelkom University1
Ali MuhammadUniversitas PGRI Kalimantan1
Soni YoraTelkom University1

Affiliations come from OpenAlex; journal OAI-PMH metadata carries none. Authors without an OpenAlex ID are matched by name, which can merge or split people.

Metadata source: OAI-PMH (metadata jurnal) https://jiki.cs.ui.ac.id/index.php/jiki/oai, first harvested 26 Okt 2026, last seen 26 Okt 2026.
Original metadata (oai_dc) 
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	<dc:title xml:lang="en-US">Bimodal Keystroke Dynamics-Based Authentication for Mobile Application Using Anagram</dc:title>
	<dc:creator>Yunanto, Prasti Eko</dc:creator>
	<dc:creator>Barmawi, Ari Moesriami</dc:creator>
	<dc:subject xml:lang="en-US">biometrics</dc:subject>
	<dc:subject xml:lang="en-US">keystroke dynamic</dc:subject>
	<dc:subject xml:lang="en-US">identification</dc:subject>
	<dc:subject xml:lang="en-US">authentication</dc:subject>
	<dc:description xml:lang="en-US">Currently, most of the smartphones recognize uses based on static biometrics, such as face and fingerprint. However, those traits were vulnerable against spoofing attack. For overcoming this problem, dynamic biometrics like the keystroke and gaze are introduced since it is more resistant against spoofing attack. This research focuses on keystroke dynamics for strengthening the user recognition system against spoofing attacks. For recognizing a user, the user keystrokes feature used in the login process is compared with keystroke features stored in the keystroke features database. For evaluating the accuracy of the proposed system, words generated based on the Indonesian anagram are used. Furthermore, for conducting the experiment, 34 participants were asked to type a set of words using the smartphone keyboard. Then, each user’s keystroke is recorded. The keystroke dynamic feature consists of latency and digraph which are extracted from the record. According to the experiment result, the error of the proposed method is decreased by 23.075% of EER with FAR and FRR are decreased by 16.381% and 10.41% respectively, compared with Kim’s method. It means that the proposed method is successful increase the biometrics performance by reducing the error rates</dc:description>
	<dc:publisher xml:lang="en-US">Faculty of Computer Science  - Universitas Indonesia</dc:publisher>
	<dc:date>2022-07-02</dc:date>
	<dc:type>info:eu-repo/semantics/article</dc:type>
	<dc:type>info:eu-repo/semantics/publishedVersion</dc:type>
	<dc:format>application/pdf</dc:format>
	<dc:identifier>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/1015</dc:identifier>
	<dc:identifier>10.21609/jiki.v15i2.1015</dc:identifier>
	<dc:source xml:lang="en-US">Jurnal Ilmu Komputer dan Informasi; Vol. 15 No. 2 (2022): Jurnal Ilmu Komputer dan Informasi (Journal of Computer Science and Information); 81-91</dc:source>
	<dc:source>2502-9274</dc:source>
	<dc:source>2088-7051</dc:source>
	<dc:source>10.21609/jiki.v15i2</dc:source>
	<dc:language>eng</dc:language>
	<dc:relation>https://jiki.cs.ui.ac.id/index.php/jiki/article/view/1015/459</dc:relation>
	<dc:rights xml:lang="en-US">Copyright (c) 2022 Jurnal Ilmu Komputer dan Informasi</dc:rights>
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