基于模糊影响图的差分隐私算法保护效果评估方法

Assessment method on protection effectiveness of differential privacy algorithms based on fuzzy influence diagram

针对隐私保护算法实际保护效果评估难的问题,提出了一种基于模糊影响图的差分隐私算法保护效果评估方法,实现对差分隐私算法的多维度评估,得出保护效果综合分数和等级。从算法安全性、算法可行性、隐私偏差性、数据可用性和用户体验5个方面出发,建立指标体系。使用模糊理论处理不确定性,通过影响图传递影响关系并计算该模糊影响图,得出保护效果分数和等级,据此反馈调整算法参数,实现迭代评估。提出正向化环节,解决截然相反的算法在某些情况下评估结果一样的问题。电-碳模型中的对比实验表明,所提方法能够对差分隐私算法的保护效果做出有效评价,消融实验进一步表明,正向化环节对算法的区分度起了关键作用。

In response to the challenge of comprehensively assessing privacy-preserving algorithms,an assessment method on protection effectiveness of differential privacy algorithms based on fuzzy influence diagram was proposed,achieving a multi-perspective assessment of differential privacy algorithms with a comprehensive score and level as as‐sessment results.Starting from five aspects—algorithm security,feasibility,privacy bias,data utility,and user experi‐ence,an indicator system was established.Fuzzy theory was employed to handle uncertainties,while the diagram was used to propagate interactions between factors.The assessment score and level were obtained by calculating the fuzzy in‐fluence diagram,and then used as feedback for parameter adjustment to achieve iterative assessment.Formalization link was proposed to solve the problem of completely opposite algorithms with idential evaluation results.Comparative ex‐periments on electricity-carbon analysis model demonstrate the proposed method can assess the protection effectiveness of differential privacy algorithms effectively.Ablation experiments further show that the formalization link plays a key role in the discrimination of the algorithm.