A Secure Distributed Framework for Agglomerative Hierarchical Clustering Construction
A Secure Distributed Framework for Agglomerative Hierarchical Clustering Construction
复制标题
一种用于聚合层次聚类构建的安全分布式框架
DOI：
10.1109/pdp2018.2018.00075
复制
发表时间：
2018
期刊：
影响因子：
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通讯作者：
F. Martinelli
中科院分区：
文献类型：
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作者：
M. Hamidi;M. Alishahi;F. Martinelli
本文提出了一个通用的框架，用于构建任何凝聚层次聚类算法在分区数据。假设数据在两个（或多个）方之间水平分布，使得为了共同利益，参与方愿意在其数据上整体地识别集群的结构，但是出于隐私限制，他们避免共享原始数据集。为此，在这项研究中，我们提出了一般算法的基础上安全的标量积和安全的汉明距离计算安全地计算所需的标准，塑造集群的计划。所提出的方法涵盖了所有可能的安全凝聚层次聚类结构时，数据分布在两个（或更多）方，包括数值和分类数据。
This paper presents a general framework for constructing any agglomerative hierarchical clustering algorithm over partitioned data. It is assumed that data is distributed between two (or more) parties horizontally, such that for mutual benefits the participated parties are willing to identify the clusters' structure on their data as a whole, but for privacy restrictions, they avoid to share the original datasets. To this end, in this study, we propose general algorithms based on secure scalar product and secure hamming distance computation to securely compute the desired criteria for shaping the clusters' scheme. The proposed approach covers all possible secure agglomerative hierarchical clustering construction when data is distributed between two (or more) parties, including both numerical and categorical data.