AI-Powered Network Intrusion Detection System An intelligent, real-time network intrusion detection system built with deep learning. It uses a CNN-LSTM hybrid neural network trained on the NSL-KDD benchmark dataset to automatically classify network traffic into five categories: Normal, DoS (Denial of Service), Probe, R2L (Remote-to-Local), and U2R (User-to-Root) attacks. The system features a sleek, modern web interface with a glassmorphic design, secure user authentication, and an interactive dashboard where users can input network traffic features and receive instant predictions with full confidence breakdowns across all threat classes. Key Highlights: - Deep Learning Powered: Multi-layer 1D Convolutional Neural Network combined with LSTM for temporal pattern recognition in network traffic, achieving 99% training accuracy. - Real-Time Threat Detection: Analyze network packets on the fly and receive predictions in under 100ms, enabling rapid threat identification and response. - 5-Class Attack Classification: Classifies traffic into DoS, Probe, R2L, U2R, or Normal — covering the most critical categories of network intrusions. - Secure Access: User registration and login with bcrypt-hashed passwords and session-based authentication to protect the dashboard and prediction endpoints. - Probability Breakdown: Every prediction comes with a full confidence distribution across all five threat classes, giving complete transparency into the model's decision. - Modern Web Dashboard: Beautiful, responsive UI with animated glassmorphism effects, interactive charts, and a clean user experience built with vanilla HTML, CSS, and JavaScript. - REST API: Programmatic access to the prediction engine via a JSON-based API endpoint for integration with external tools and automation pipelines. Technology Stack: - Backend: Python, Flask, TensorFlow/Keras - Frontend: HTML5, CSS3 (Glassmorphism), JavaScript - Machine Learning: CNN-LSTM Hybrid Model, Scikit-learn (preprocessing) - Database: SQLite3 (user authentication) - Dataset: NSL-KDD (Canadian Institute for Cybersecurity) - Security: bcrypt password hashing, session-based auth Built for cybersecurity researchers, network administrators, and anyone looking to leverage AI for proactive network defense.