This project aims to develop a behavioral biometrics-based continuous authentication system that verifies user trustworthiness based on typing patterns, mouse movements, and interaction behavior.
Study behavioral biometrics and continuous authentication concepts.
Identify behavioral signals such as keystroke dynamics.
Design system architecture for behavioral data collection.
Implement real-time pattern analysis algorithms.
Train machine learning models for user profiling.
Compare authentication accuracy with traditional login systems.
Detect session hijacking attempts.
Measure false acceptance and rejection rates.
Evaluate usability impact of continuous monitoring.
Ensure privacy protection of behavioral data.
Document security and ethical considerations.
