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このアイテムの引用には次の識別子を使用してください: http://hdl.handle.net/10119/9748

タイトル: Privacy Preserving Frequency Mining in 2-Part Fully Distributed Setting
著者: LUONG, The Dung
HO, Tu Bao
キーワード: privacy preserving frequency mining
2-part fully distributed setting
cryptography
発行日: 2010-10-01
出版者: 電子情報通信学会
誌名: IEICE TRANSACTIONS on Information and Systems
巻: E93-D
号: 10
開始ページ: 2702
終了ページ: 2708
DOI: 10.1587/transinf.E93.D.2702
抄録: Recently, privacy preservation has become one of the key issues in data mining. In many data mining applications, computing frequencies of values or tuples of values in a data set is a fundamental operation repeatedly used. Within the context of privacy preserving data mining, several privacy preserving frequency mining solutions have been proposed. These solutions are crucial steps in many privacy preserving data mining tasks. Each solution was provided for a particular distributed data scenario. In this paper, we consider privacy preserving frequency mining in a so-called 2-part fully distributed setting. In this scenario, the dataset is distributed across a large number of users in which each record is owned by two different users, one user only knows the values for a subset of attributes, while the other knows the values for the remaining attributes. A miner aims to compute the frequencies of values or tuples of values while preserving each user's privacy. Some solutions based on randomization techniques can address this problem, but suffer from the tradeoff between privacy and accuracy. We develop a cryptographic protocol for privacy preserving frequency mining, which ensures each user's privacy without loss of accuracy. The experimental results show that our protocol is efficient as well.
Rights: Copyright (C)2010 IEICE. The Dung LUONG, Tu Bao HO, IEICE TRANSACTIONS on Information and Systems, E93-D(10), 2010, 2702-2708. http://www.ieice.org/jpn/trans_online/
URI: http://hdl.handle.net/10119/9748
資料タイプ: publisher
出現コレクション:a10-1. 雑誌掲載論文 (Journal Articles)

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