Keystroke Dynamics in Behavioral Biometrics for User Authentication

Information Science and Engineering

The goal of behavioral biometrics analysis is to record distinct user interactions, including typing dynamics (speed, rhythm, and pressure), device handling patterns (swiping motions, grip angle), and even gait traits based on walking style. By forming a strong layer of identity verification, these modest, unique characteristics successfully reduce the dangers of identity theft and cyber fraud. Our cutting-edge multi-factor authentication system is a hybrid method that improves security while maintaining user ease by fusing facial recognition and behavioral analytics. Modern machine learning algorithms provide quick and accurate verification by processing and comparing real-time data with pre-established user profiles. To protect against fraudulent efforts and maintain system resilience, anti-spoofing techniques are integrated. Its usefulness and adaptability are confirmed by extensive testing in a variety of settings and scenarios. Putting a lot of focus on user Keystroke Dynamics in Behavioral Biometrics for User Authentication

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.