Differentially Private Hierarchical Count-of-Counts Histograms
Differentially Private Hierarchical Count-of-Counts Histograms
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DOI：
10.14778/3236187.3236202
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发表时间：
2018-04
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影响因子：
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通讯作者：
Yu-Hsuan Kuo;Cho-Chun Chiu;Daniel Kifer;Michael Hay;Ashwin Machanavajjhala
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文献类型：
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作者：
Yu-Hsuan Kuo;Cho-Chun Chiu;Daniel Kifer;Michael Hay;Ashwin Machanavajjhala
我们考虑私下释放一类查询的问题，我们称之为分层计数直方图。Count-of-counts直方图将输入表的行划分为组（例如，同一家庭中的一组人），并且对于每个整数j报告大小为j的组的数量。分层计数查询根据输入数据中属性定义的层次结构（例如，家庭在国家、州和县级别的地理位置），以不同粒度报告计数直方图。在本文中，我们介绍了这个问题，以及适当的误差度量，并提出了一个差分私有解决方案，该解决方案生成了在层次结构的所有级别上一致的计数直方图。
We consider the problem of privately releasing a class of queries that we call hierarchical count-of-counts histograms . Count-of-counts histograms partition the rows of an input table into groups (e.g., group of people in the same household), and for every integer j report the number of groups of size j . Hierarchical count-of-counts queries report count-of-counts histograms at different granularities as per hierarchy defined on an attribute in the input data (e.g., geographical location of a household at the national, state and county levels). In this paper, we introduce this problem, along with appropriate error metrics and propose a differentially private solution that generates count-of-counts histograms that are consistent across all levels of the hierarchy.