基于聚类匿名化的差分隐私保护数据发布方法

doi:10.11959/j.issn.1000-436x.2016100

Abstract

Abstract:

Based on the theory of anonymization,the DBSCAN method was applied to divide all the data records into different groups to cover individuals.To provide priv enhancement,the Laplace noise was added to the anonymized partitioned data to perturb the real value of data record so that the requirements of differential privacy model were satis-fied.With the clustering operation,the sensitivity of the query function has been partitioned to improve data utility.The proof of privacy has been given and experimental results have been provided to evaluate the utility of the released data.

Key words: differential privacy, privacy preservation, clustering, data release, anonymization

Xiao-qian LIU,Qian-mu LI. Differentially private data release based on clustering anonymization[J]. Journal on Communications, 2016, 37(5): 125-129.

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数据集名称	数据集标识符	属性个数	数据记录数目	数据类型
MAGIC Gamma Telescope Data Set	DS	10	1 012	real

Differentially private data release based on clustering anonymization

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