A Robust Authentication Algorithm for Medical Images Based on Fractal Brownian Model and Visual Cryptography

TLDR: A security authentication method is designed based on fractal and visual cryptography based on the discrete fractal Brownian random field model that is effective against common attacks such as JPEG compression, scaling, rotation operation, clipping, added noise, filtering, and blurring.

Abstract: In this paper, we aimed to discuss the security authentication requirements of medical images in the medical network, and a security authentication method is designed based on fractal and visual cryptography. Based on the discrete fractal Brownian random field model, the gray-level statistical information and spatial structure information of medical images is fully mined. The gray distribution of medical images is expressed in the form of fractal features. By using the spatial data mining methods, the data of fractal structure space is analyzed, and by using the stability of the energy structure, the authentication features are formed. Using the visual cryptography (VC), the robustness of the authentication method is further enhanced. Through the centralized test of common medical images and the comparison analysis with existing methods, it is further verified that the method is effective against common attacks such as JPEG compression, scaling, rotation operation, clipping, added noise, filtering, and blurring.