https://github.com/shubhampaliwal03/traffictracer
A web application for botnet detection using Machine Learning - XGBoost, from the csv file containing network packet flows, captured using CICFlowMeter Tool.
https://github.com/shubhampaliwal03/traffictracer
Last synced: 10 days ago
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A web application for botnet detection using Machine Learning - XGBoost, from the csv file containing network packet flows, captured using CICFlowMeter Tool.
- Host: GitHub
- URL: https://github.com/shubhampaliwal03/traffictracer
- Owner: ShubhamPaliwal03
- Created: 2025-05-02T22:09:28.000Z (20 days ago)
- Default Branch: main
- Last Pushed: 2025-05-02T22:33:19.000Z (20 days ago)
- Last Synced: 2025-05-02T23:26:20.174Z (20 days ago)
- Language: HTML
- Size: 15.3 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
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Metadata Files:
- Readme: README.md
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README
# TrafficTracer 📦🔍
A web application for botnet detection using Machine Learning - XGBoost, from the csv file containing network packet flows, captured using CICFlowMeter Tool.
**TrafficTracer** allows users to upload CSV files containing extracted network flow data and instantly receive detection results indicating whether the traffic is normal or part of a botnet. The system processes the uploaded file, runs it through a pre-trained machine learning model, and visualizes the output using intuitive charts and tables for easy interpretation.
To assist users in generating flow-based CSV files, a downloadable `.jar` file of **CICFlowMeter** is also provided along with usage instructions, enabling users to perform local packet capture and feature extraction before uploading to the web app.
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### Tech Stack
- **Frontend:** HTML, CSS, JavaScript, Chart.js
- **Backend:** FlaskAPI (Python), XGBoost model
- **Deployment:** Vercel (Frontend), Render.com (Backend API)
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This app is designed for simplicity and quick analysis, making botnet detection accessible to users without deep technical expertise.