This repository contains practical code examples demonstrating the use of Artificial Intelligence (AI) techniques—Computer Vision, Deep Learning, and Reinforcement Learning—for cybersecurity applications in space orbiters.
-
computer_vision/
Contains scripts for anomaly detection in orbital images using OpenCV. -
deep_learning/
Contains a simple neural network implementation using TensorFlow/Keras to classify telemetry data as normal or anomalous. -
reinforcement_learning/
Contains a Q-learning example simulating adaptive decision-making for cyber defense strategies.
- Python 3.7+
- OpenCV (
pip install opencv-python) - TensorFlow (
pip install tensorflow) - NumPy (
pip install numpy)
Each folder contains a Python script illustrating the corresponding AI technique.
Example:
python anomaly_detection.py # under computer_vision/ python telemetry_classification.py # under deep_learning/ python adaptive_defense_rl.py # under reinforcement_learning/
Refer to individual scripts for detailed comments.
MIT License
PV-J (github.com/PV-J)