Chaotic cosine and logistic map based robust image encryption with dual-stage confusion-diffusion architecture

Area of Science:

• Computer Science
• Cryptography
• Information Security

Background:

• Secure data transmission is critical in big data environments.
• Existing encryption methods may be computationally intensive for resource-constrained systems.
• Need for efficient and robust image encryption algorithms.

Purpose of the Study:

• To propose an efficient and robust image encryption algorithm for secure data transmission.
• To leverage chaotic systems for enhanced randomness and security.
• To ensure suitability for resource-constrained big data environments.

Main Methods:

• Utilized a cosine extended logistic chaotic map with verified dynamics (bifurcation, Lyapunov exponents, entropy).
• Implemented a two-phase confusion and two-phase diffusion process.
• Incorporated techniques: chaotic pixel permutation, controlled flipping, modulo arithmetic, MSB/LSB separation, cross quadrant bitwise operations.

Main Results:

• Achieved near-ideal entropy (~7.997), high NPCR (~99.6094%) and UACI (~33.4635%).
• Demonstrated strong resistance against statistical and differential attacks (low chi-square and correlation values).
• Key space estimated at 2^318, exceeding brute-force resilience standards.

Conclusions:

• The proposed algorithm offers a lightweight yet robust solution for image encryption.
• It provides a strong balance between security and computational efficiency.
• Suitable for real-time image transmission in big data and resource-constrained settings.