关键词: 隐私保护, 匿名, 微聚集, 隐私泄露, 差分隐私

Abstract: There exists the problem of security insufficience among the data privacy protecting technology which is the privacy leakage caused by homogeneity and background knowledge attack when computing equivalence classes in the anonymity process. To solve the problem, an anonymized data privacy protection method based on differential privacy was put forward, and its model was constructed. ε-MDAV (Maximum Distance to Average Vector) algorithm was presented, in which micro-aggregation MDAV algorithm was used to partition similar equivalence classes, and SuLQ frame framework was introduced into the anonymous attribute process. Laplace mechanism was used to reasonably control the privacy protection budget. The comparison of availability and security under different privacy protect budgets verifies that the proposed method effectively improve data security while guaranteeing high data availability.

Key words: privacy protection, anonymity, micro-aggregation, privacy leakage, differential privacy