With the increasing need for secure image transmission, encryption techniques play a vital role in cybersecurity. This project explores Genetic Algorithm-based Image Encryption, integrating mutation, crossover, and selection techniques to evolve encrypted images while ensuring security and randomness.
Additionally, we compare the performance of AES (Advanced Encryption Standard) and DES (Data Encryption Standard) with the Genetic Algorithm-based encryption to highlight differences in security strength.
- Python (NumPy, OpenCV, Matplotlib)
- Genetic Algorithm (GA) (Selection, Crossover, Mutation)
- AES & DES Encryption
- Randomized Pixel Transformation
- Tournament Selection & Fitness Function Analysis
✅ Develop a Genetic Algorithm-based Image Encryption System
✅ Improve security by randomizing pixel values
✅ Compare GA-based encryption with AES & DES
✅ Ensure robustness and unpredictability in image encryption
🔹 Genetic Algorithm-Based Encryption:
- Applies mutation (random pixel transformations)
- Uses crossover techniques for encryption diversity
- Employs tournament selection for best encryption candidates
🔹 AES & DES Integration:
- Compares standard encryption algorithms with GA-based encryption
- Evaluates security and computational efficiency
🔹 Security & Performance Evaluation:
- Measures encryption randomness
- Tests decryption accuracy
- Analyzes image reconstruction quality
- Clone the repository:
git clone https://github.com/yourusername/image-encryption-ga.git