Evaluating the Security of a "Blind Quantum Algorithm-centered Medical Privacy Data Sharing Model" Using the DHGF Method

The classical algorithm, renowned for its mature technology, effective application, and high reliability, is utilized to verify the safety of a model constructed with quantum algorithms and technologies as its core. This demonstrates a pioneering effort to extend the application of classical algorithms into the quantum domain. A case study involving the " Blind Quantum Algorithm-centered Medical Privacy Data Sharing Model " is employed to illustrate the entire process of evaluating the security of a private data model using the DHGF classical algorithm. The evaluation index system for the " Blind Quantum Algorithm-centered Medical Privacy Data Sharing Model" is established using the Delphi method. The hierarchical framework of the evaluation index system is derived via the analytic hierarchy process, and the weight coefficients are determined by pairwise comparison of each component factor's importance. The Grey analysis method is then utilized to construct an evaluation sample matrix, with grey clustering being determined through grey theory and grey statistics, accompanied by the calculation of a fuzzy weight matrix. Subsequently, the fuzzy evaluation computes the comprehensive evaluation value, resulting in a classification indicating that the model's safety level is high. These findings demonstrate that the proposed algorithm effectively captures the security dynamics of the model and presents a novel solution for analyzing the security of complex models with uncertainty.