Analysis of user identification methods in web browsers
Website visitor data helps to increase application security, control limited access, personalize content, collect data and improve the application. The article analyzes user identification methods in a browser: Browser Fingerprint, Supercookie, Keystroke Dynamics. The analysis of the methods was perfomed based on 4 criteria: False Acceptance Rate, applicability, avoidance resistance, Frontend Performance. For the research, literature, tests in different browsers, demo scripts in JavaScript, and the Performance API were used. It has been shown that the Supercookie is ineffective today, but Browser Fingerprint and Keystroke Dynamics can still be utilized for identification.
Authors
- Jakub Smółka (ORCID: https://orcid.org/0000-0002-8350-2537)
- Eduard Chyzhik
Institutions
- Lublin University of Technology (PL)
Publication Details
- Journal
- Journal of Computer Sciences Institute
- Published
- 2025-03-30
- DOI
- https://doi.org/10.35784/jcsi.6701
- Primary Topic
- User Authentication and Security Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00