Enhancing grayscale image encryption through Petri net dynamics and hash-extracted keystreams

The rapid advancement of digital communication underscores the necessity for secure image transmission. Traditional encryption methods often fall short in addressing the unique challenges posed by image data, such as high redundancy and inter-pixel correlations. This study introduces a novel Petri net-based encryption scheme for grayscale images, leveraging the deterministic evolution of Petri nets to generate high-entropy keystreams. By integrating the SHA-256 hash function, the scheme extracts keystream bytes from the evolved Petri net states. Our approach incorporates a cipher-feedback mechanism to enhance diffusion, thereby fortifying resistance against differential and chosen-plaintext attacks. Extensive evaluations, including NIST STS tests, entropy analysis, and correlation assessments, demonstrate the robustness and effectiveness of our method. The results reveal near-ideal entropy levels, minimal adjacent pixel correlations, and strong diffusion properties, confirming the practicality and security of the proposed Petri net-based encryption scheme for grayscale images.