Network-Anomaly-Detection-System using Streamlit

The system relies on:

Collecting and analyzing data using the LUFlow dataset (benign, malicious, outlier).

Training an ANN model using Keras to achieve high accuracy and reduce false positives.

Developing an interactive interface with Streamlit to monitor live traffic via Tshark.

How to Run

1. Install dependencies: pip install -r requirements.txt

2. ReadMe-If-Python-Venv.txt or ReadMe-If-anaconda.txt