Mobile Educational Application for Keystroke Dynamics Identification Systems

Renat Haluska*, Dominik Molcanyi*, Matus Pleva*, Daniel Hladek*, Jan Stas*, Ming Hsian Su, Yuan Fu Liao

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

This paper describes a chosen biometric method used in biometric systems to identify the user during online education interaction. The current demo page of the system is text-dependent, and it is planned to improve the identification and authentication mechanism to support continuous authentication and be able to detect cheating during online written exams. The article describes the keystroke dynamics method and informs the reader of current trends using this method and the implementation of keystroke dynamics within a web application used in an educational biometrics class.

Original languageEnglish
Title of host publicationICETA 2023 - 21st Year of International Conference on Emerging eLearning Technologies and Applications, Proceedings
EditorsStefan Fejedelem
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages165-170
Number of pages6
ISBN (Electronic)9798350370690
DOIs
StatePublished - 2023
Event21st International Conference on Emerging eLearning Technologies and Applications, ICETA 2023 - Stary Smokovec, Slovakia
Duration: 26 Oct 202327 Oct 2023

Publication series

NameICETA 2023 - 21st Year of International Conference on Emerging eLearning Technologies and Applications, Proceedings

Conference

Conference21st International Conference on Emerging eLearning Technologies and Applications, ICETA 2023
Country/TerritorySlovakia
CityStary Smokovec
Period26/10/2327/10/23

Keywords

  • biometrics
  • educational application
  • keystroke dynamics
  • mobile application
  • user identification

Fingerprint

Dive into the research topics of 'Mobile Educational Application for Keystroke Dynamics Identification Systems'. Together they form a unique fingerprint.

Cite this