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

Resumo

This research addresses the academic challenge of lacking security verification methods for quantum computing models. It innovatively introduces the DHGF comprehensive evaluation method into the quantum security field, successfully overcoming the adaptability bottleneck of traditional evaluation methods in quantum scenarios. The research proposes a cross-verification method between a classical algorithm-based evaluation system and a quantum security model, constructing a methodological framework for cross-validation between classical algorithms and quantum technology. This enables dynamic evaluation of blind quantum computing protocols using the DHGF comprehensive evaluation method. Taking a "Blind Quantum Algorithm-centered Medical Privacy Data Sharing Model" as an example, the research demonstrates the entire process of evaluating the security of a privacy data model built on quantum algorithms and technology using the classical DHGF comprehensive evaluation method. The evaluation process integrates the Delphi method, Analytic Hierarchy Process, Grey System Theory, and Fuzzy Comprehensive Evaluation. The Delphi method is used to determine the evaluation indicator set based on expert opinions; the Analytic Hierarchy Process is employed to determine the weights of the evaluation indicators; and then the evaluation is conducted using the Grey System Theory and Fuzzy Comprehensive Evaluation. This research leverages mature and reliable classical algorithms to validate the security of a model built using quantum algorithms and technologies as its core. This approach establishes a cross-validation system integrating classical and quantum techniques, resulting in a dynamically scalable paradigm for quantum security assessment. This represents a bold extension of classical algorithms into the quantum domain. The comprehensive evaluation score Z from the research results demonstrates the algorithm's ability to accurately and quantitatively describe the dynamic security of the model, providing a novel solution for security analysis of complex and uncertain models and holding significant practical value.