Keystroke Dynamics Based Authentication System


Çevik N., Akleylek S., Koç K. Y.

6th International Conference on Computer Science and Engineering, UBMK 2021, Ankara, Turkey, 15 - 17 September 2021, pp.644-649 identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/ubmk52708.2021.9559008
  • City: Ankara
  • Country: Turkey
  • Page Numbers: pp.644-649
  • Keywords: Behavioral biometrics, Keystroke dynamics, Machine learning, Two-factor authentication
  • Ondokuz Mayıs University Affiliated: Yes

Abstract

Nowadays, many companies use biometrie technologies for the security of critical systems as well as usernamepassword methods. In the literature, biometrie systems are the most commonly used systems among the two-factor authentication systems. There are two different approaches to biometrie systems: physical and behavioral biometrie systems. In the last decade, the accuracy of behavioral biometrie systems has significantly increased with the use of machine learning methods in these systems. For this reason, the usage areas of the studies in this field have expanded. In this study, we focus on keystroke dynamics based on behavioral methods. Firstly, we make a web application to collect keystroke data from 54 employees in a company. Then, we use the benchmark database and our database to train-test machine learning algorithms, which have the highest accuracy in this field in the literature. Among them, tree-based algorithms have the highest accuracy score, with an average of 0.94.