User-Behavior-Anomaly-Detection-System

🎯 Inspiration Security monitoring needs in modern web applications Detection of insider threats and data breaches Reduction of false positives through ML Real-time monitoring capabilities 🔍 What it does Log analysis and processing capabilities Machine learning detection with Isolation Forest Interactive dashboard with visualizations Advanced features like sample data generation Security monitoring for various threat patterns 🏗️ How we built it Backend architecture with Flask and Python Frontend development with Bootstrap and Chart.js Data processing pipeline explanation Key technologies used ⚡ Challenges we ran into Technical challenges (log format variability, feature engineering) Development challenges (dependency management, cross-platform compatibility) Solutions implemented for each challenge 🏆 Accomplishments that we're proud of Technical achievements (feature engineering, anomaly detection) User experience improvements System integration capabilities

Built With

• python