差异化多敏感属性Lq-Diversity模型和算法

针对多维敏感属性数据发布面临的一般泄露、交叉泄露、相似性泄露、多维独立泄露的威胁,本文提出了敏感属性敏感等级和敏感属性值敏感等级的概念,基于单维l-diversity模型,对各维敏感属性进行单独分组,提出了差异化多维敏感属性模型,验证了该模型在面向多敏感属性数据发布的安全性,并根据此模型提出了相应的DMSA算法,通过实验验证,该算法正确可行,且隐匿率和附加信息损失度的值都很低,数据可用性高,具有良好的隐私保护效果.

Lq-Diversity Model and Algorithm of Differentiated Multisensitive Property

According to the threats of general leakage, cross leakage, similar leakage and multidimensional independent leakage in redistribution of data of multi sensitive attributes, this paper puts forward the concept of sensitive attribute sensitivity level and sensitivity level of sensitive attribute values. Then, it separates each dimension of sensitive attributes based on l-diversity model. It also puts forward the lq-diversity model of differentiated multi sensitive property. Experiments prove that it is safe for the distribution of data of multiple sensitive attributes. Finally, according to lq-diversity model, the paper puts forward a corresponding DMSA algorithm, which is proved to be correct and feasible, and has low occult rate and loss degree of additional information. The result indicates data has high availability and good privacy after released with this method.