Real-time Anomaly Detection for Network Intrusions

Project information

Real-time Anomaly Detection for Network Intrusions

Developed a real-time anomaly detection system using Python and TensorFlow to identify potential network intrusions.

Employed streaming libraries (like Streamlit) to process network traffic data in real-time, enabling faster threat detection and response.

Visualized anomalies through interactive dashboards for efficient security monitoring.