Cellular automata based key distribution for lightweight hybrid image encryption with elliptic curve cryptography

Area of Science:

• Computer Science
• Cryptography
• Internet of Things (IoT)

Background:

• IoT devices require secure and efficient data encryption due to limited resources.
• Existing encryption methods may not be suitable for the constraints of IoT environments.
• Hybrid encryption schemes offer a balance of security and performance.

Purpose of the Study:

• To propose a lightweight hybrid image encryption scheme tailored for IoT applications.
• To enhance the security and efficiency of image encryption in resource-constrained environments.
• To validate the scheme's effectiveness through rigorous testing and analysis.

Main Methods:

• Secure key exchange is performed using Elliptic Curve Cryptography (ECC).
• Random keys are generated using a Cellular Automata (CA) Rule Vector seeded by ECC-exchanged secrets.
• Image encryption is achieved using the Advanced Encryption Standard (AES-128) algorithm.

Main Results:

• The proposed scheme demonstrates strong security with high NPCR (99.6461) and UACI (49.9927) values.
• The encryption process achieved an entropy of 7.9991 for the Baboon Image, indicating high data diffusion.
• The method successfully passed all NIST randomness tests and exhibited superior execution time compared to existing solutions.
• The generated keys showed high dispersion and security, suitable for AES encryption.

Conclusions:

• The lightweight hybrid image encryption scheme is highly suitable for resource-constrained IoT environments.
• The integration of ECC, CA, and AES provides a robust and efficient solution for IoT image security.
• The scheme offers a practical approach to securing sensitive image data in IoT applications.