Dynamic Security Computing Framework With Zero Trust Based on Privacy Domain Prevention and Control Theory

作者：Xiang Wu, Baowen Zou, Chengpeng Lu, Lili Wang, Yongting Zhang, Huanhuan Wang · 发表于：IEEE Journal on Selected Areas in Communications · 年份：2025 · DOI：10.1109/jsac.2025.3560036 · 被引用次数：54 · 研究领域：Access Control and Trust、Cloud Data Security Solutions

With a growing security threat in wireless communication networks, a promising method for secure next-generation networks is a zero-trust framework focusing on authentication schemes. How to analyze the risks involved in authentication is a challenge. This study quantifies authentication risks within the zero-trust framework and introduces a privacy domain prevention-control theory. The theory encompasses dynamic privacy risk assessment, intelligent risk classification, and automated selection of privacy protection schemes. First, a dynamic privacy risk assessment method, based on physical entity relationships, is proposed to evaluate all privacy risks. Second, a five-category risk classification method is designed to categorize privacy risks, facilitating the selection of prevention-control schemes, with its rationality mathematically validated. Additionally, an Analytical Hierarchy Process (AHP)-based method is introduced to guide the optimal selection of prevention-control schemes for various scenarios. Finally, the practical application of the theory in medicine multi-modal computing scene of wireless body area networks demonstrates its effectiveness. The experimental results also show the superiority and feasibility of the proposed methods.