An enhanced Lorenz-based chaos cryptographic scheme with modular arithmetic and prime masking

Abstract

Chaos theory has nowadays plays as a strong and useful tool in the current digital world. It provides a somewhat reliable way of securing data in digital form, such as image data, through unpredictable deterministic systems. In this study, we introduce a new encryption method that combines the chaotic Lorenz system with modular arithmetic and prime masking for image data encryption. The chaotic nature of the Lorenz system’s outputs is known to be highly sensitive to initial conditions, and therefore forms the foundation of our key stream for the encryption. Then the modular arithmetic in a finite field  is used to increase robustness of the encryption; moreover, followed by prime-masking, thereby adding a nonlinear security layer of confusion as appropriate. This triple-layered encryption approach strengthens resistance to the current prevalence of statistical attacks. Our implementation and experiments on coloured images demonstrate, significantly, strong randomness, high entropy, and negligible pixel correlation in the encrypted result, while maintaining efficient decryption. Upon comparisons with traditional methods, such as Advanced Encryption Standard (AES), reveal that the proposed scheme offers unique strengths in lightweight and dynamic encryption. This approach is especially suitable for constrained applications such as IoT environments. The new hybridization combines chaos theory with algebraic masking to achieve both simplicity and strong security.