摘要： 现有匿名算法多数仅针对准标识符进行泛化实现隐私保护,未考虑敏感属性的个性化保护问题。为此,在p-sensitive k匿名模型的基础上设计敏感属性个性化隐私保护算法。根据用户自身的敏感程度定义敏感属性的敏感等级,利用敏感属性泛化树发布精度较低的敏感属性值,从而实现对敏感属性的个性化保护。实验结果表明,该算法可有效缩短执行时间,减少信息损失量,同时满足敏感属性个性化保护的要求。

关键词: p-sensitive k匿名模型, 个性化隐私保护, 敏感属性, 泛化, 用户评分

Abstract: Most of the existing anonymous algorithms only implement the privacy protection by quasi-identifier generalization,which do not consider personalized protection issues of the sensitive attribute.Aiming at this problem,by using the p-sensitive k-anonymity model,this paper designs a personalized privacy protection algorithm based on sensitive attribute.It defines sensitive levels of sensitive attributes based on the user’s own sensitivity and uses sensitive attribute generalization tree to publish low accuracy sensitive attribute values,so as to realize the personalized protection of sensitive attribute.Experimental results show that the proposed algorithm can shorten the execution time and reduce the amount of information loss,meanwhile meeting the requirements of sensitive attribute personalized protection.

Key words: p-sensitive k-anonymity model, personalized privacy protection, sensitive attribute, generalization, user rating

中图分类号: 

• TP309