🚁 AI-Powered Military Drone Threat Detection

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🚀 Problem Statement: The Rising Threat of Rogue Drones

Modern warfare and border security face an escalating threat: rogue drones. These include:

• Kamikaze drones (suicide UAVs carrying explosives)
• Spy drones (unauthorized surveillance)
• GPS-spoofed drones (hijacked mid-flight)

Military defenses need real-time, AI-powered detection to:
✔ Identify abnormal flight patterns (sudden altitude drops, erratic movements)
✔ Distinguish friend from foe in drone swarms
✔ Trigger countermeasures (e.g., jamming, interception)

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💡 Solution: AI-Powered Anomaly Detection

This project simulates a machine learning system that:

1. Generates synthetic drone flight data (normal vs. adversarial)
2. Trains ML models to detect anomalies (unsupervised + deep learning)
3. Flags threats in real-time (simulated environment)

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🔍 Key Features

✅ Generates realistic drone datasets (normal + attack scenarios)
✅ ML approache:

• Random Forest Classification
  ✅ Military-focused threat detection:
• GPS spoofing, kamikaze dives, swarm infiltration
  ✅ Scalable to real-time systems