Behavioral Biometrics-based Continuous User Authentication

The field of cybersecurity is exploring new ways to defend against cyber-attacks, including a technique called continuous user authentication. This method uses keystroke (typing) data to continuously match the user\u27s typing pattern with patterns previously recorded using artificial intelligence (AI) to identify the user. While this approach has the potential to improve security, it also has some challenges, including the time it takes to register a user, the performance of machine learning algorithms on real-world data, and latency within the system. In this study, the researchers proposed solutions to these issues by using transfer learning to reduce user registration time, testing machine learning algorithms on real-world data, and developing a universal benchmarking framework to evaluate databases in practical situations. The results of the experiments supported the researchers\u27 observations and suggestions for improving continuous user authentication