🚀 Project ARTEMIS: A Smart Cybersecurity Framework

A multi-layered cybersecurity defense system combining Machine Learning, Threat Intelligence, Web Application Firewall (WAF), and Incident Response Planning. Proactive, scalable, and modular! 🛡️

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📂 Repository Structure

├── DDOS/
│   ├── dataset/              # Dataset for DDoS detection model
│   └── code.py               # ML model to detect DDoS attacks
│
├── Incident Response Plan/
│   └── IRP.pdf               # Incident Response Plan (IRP) document
│
├── Phishing/
│   ├── phishing_ml_code.py   # ML model for phishing detection
│   └── server.py             # Backend server for phishing detection
│
├── WAF/
│   ├── inputpage.html        # Input form for WAF
│   └── waf_defense.py        # Python script for SQL Injection & XSS defense

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✨ Project Highlights

• DDoS Detection: Machine learning model for DDoS attack detection 🚦
• Phishing Detection: ML model + Backend server to detect phishing emails 📨
• Incident Response Plan: Professional IRP to manage cybersecurity incidents 📄
• Web Application Firewall (WAF): Protection against SQL Injection and XSS 🔒

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🎯 Objectives

• Simulate real-world cyber threats like Wi-Fi deauthentication attacks
• Build ML models for phishing and DDoS detection
• Gather threat intelligence using AWS-hosted honeypots
• Design a scalable and actionable Incident Response Plan (IRP)
• Provide real-time alerts and easy-to-use dashboards

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🛠️ Technologies Used

• Python 🐍
• Scikit-learn, XGBoost
• AWS Cloud
• ELK Stack (Elasticsearch, Logstash, Kibana)
• HTML (for WAF input)
• ESP8266/ESP32 microcontrollers

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📈 Results Achieved

• 90%+ accuracy in phishing and DDoS detection models 🏆
• Real-time threat visualizations using Kibana dashboards 📊
• Structured and tested Incident Response framework
• Swift, real-time threat alerts to security teams

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🧩 Unique Features

• 🛡️ Multi-Layered Security: ML detection + WAF + Honeypots + IRP
• 🔌 Modular Design: Use independently or as an integrated framework
• ⚡ Real-time Alerts: Immediate notification of threats
• 📈 Scalable Infrastructure: Cloud deployment and modular architecture
• 🔍 Proactive Threat Discovery: Wi-Fi vulnerability assessments
• 🔒 Custom-built WAF for web protection
• 🏛️ Enterprise-grade IRP based on NIST standards

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🚀 Future Enhancements

• Integrate SOAR platforms for automated threat mitigation
• Add User Behavior Analytics (UEBA) for anomaly detection
• Enhance threat dashboards with predictive analytics
• Expand protection to Mobile Threat Defense (MTD)

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📜 How to Use

1. DDOS Module:
   • Navigate to DDOS/ and run code.py to detect DDoS attacks.
2. Phishing Detection:
   • Navigate to Phishing/, run phishing_ml_code.py and use server.py for backend services.
3. Web Application Firewall:
   • Open inputpage.html and run waf_defense.py to protect against SQL Injection and XSS.
4. Incident Response Plan:
   • Refer to Incident Response Plan/IRP.pdf for structured incident handling.

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💬 Conclusion

Project ARTEMIS sets a new benchmark for enterprise cybersecurity by integrating threat detection, intelligence gathering, structured response, and proactive testing into a unified framework.
It empowers organizations to stay ahead of cyber threats with a future-proof security posture. 🔥

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🧠 Authors and Contributions

Made with 💻 and 💡 by the ARTEMIS Team.

Special thanks to all the contributors who made this project possible!

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© 2025 ARTEMIS Team. All Rights Reserved.