基于联合熵的多属性匿名度量模型

提出了基于联合熵的多属性匿名度量模型，该模型基于识别性、连接性、跟踪性等匿名属性．鉴于匿名的随机性和模糊性特点，提出了基于联合熵和最小加权广义距离的模糊模式识别方法，实现了系统匿名等级隶属度向量的离散化．给出了联合熵和加权广义距离之间平衡参数的确定方法．分析表明，该模型优于现有的单属性Shannon熵模型，平衡参数是从系统的角度惟一求解．因此，联合熵可以作为匿名等级的评价指标．

A Joint-Entropy-Based Anonymity Metrics Model with Multi-Property

An anonymity metrics model with three properties based on joint entropy is given in this paper. The three properties are identifiable, linkable and traceable respectively. According to randomness and fuzziness of anonymity, a fuzzy pattern recognition model is presented based on entropy and least generalized weighted distance, which makes the membership vector of anonymity grades have a desirable dispersive property. A method is proposed for computing the balance parameter between entropy and the generalized weighted distance. It is illustrated that the presented method has advantages over Shannon entropy like models in performance. The method can determine uniquely the balance parameter defined in this paper. Therefore, joint entropy is applied to evaluate the anonymity grades.