AI-driven User Behavior Analytics in Web Applications
AI-driven User Behavior Analytics (UBA) in web applications involves leveraging artificial intelligence and machine learning for real-time analysis of user activities. Key aspects include data collection, behavior profiling, anomaly detection, risk scoring, threat detection, adaptive authentication, contextual analysis, incident response automation, privacy considerations, user education, continuous learning models, IAM integration, cross-channel analysis, performance optimization, and continuous monitoring for enhanced cybersecurity and user protection.