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プライバシー保護した相関ルールマイニングに関する再考
https://ipsj.ixsq.nii.ac.jp/records/44422
https://ipsj.ixsq.nii.ac.jp/records/44422735f7b17-f71f-4051-a4b3-9d2a4804dd0d
名前 / ファイル | ライセンス | アクション |
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Copyright (c) 2007 by the Information Processing Society of Japan
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オープンアクセス |
Item type | SIG Technical Reports(1) | |||||||
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公開日 | 2007-07-19 | |||||||
タイトル | ||||||||
タイトル | プライバシー保護した相関ルールマイニングに関する再考 | |||||||
タイトル | ||||||||
言語 | en | |||||||
タイトル | Privacy-Preserving Association Rules Mining Scheme Revisited | |||||||
言語 | ||||||||
言語 | eng | |||||||
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資源タイプ識別子 | http://purl.org/coar/resource_type/c_18gh | |||||||
資源タイプ | technical report | |||||||
著者所属 | ||||||||
九州大学大学院システム情報科学府 | ||||||||
著者所属 | ||||||||
シンガポール国立情報技術研究院 | ||||||||
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シンガポール国立情報技術研究院 | ||||||||
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公立はとだて未来大学システム情報科学部 | ||||||||
著者所属 | ||||||||
九州大学大学院システム情報科学府 | ||||||||
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Department of Computer Science and Communication Engineering, Kyushu University | ||||||||
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Institute for Infocomm Research (I2R), Singapore | ||||||||
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Institute for Infocomm Research (I2R), Singapore | ||||||||
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School of Systems Information Science, Future University-Hakodate | ||||||||
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Department of Computer Science and Communication Engineering, Kyushu University | ||||||||
著者名 |
蘇春華
× 蘇春華
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著者名(英) |
Chunhua, SU
× Chunhua, SU
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論文抄録 | ||||||||
内容記述タイプ | Other | |||||||
内容記述 | Assocaition Rules Mining is a frequently used technique which finds interesting associations and correlation relationships among large set of data items that occur frequently together in varieties of social and bussiness area. For the coopertional distributed assocaition rules mining privacy-preserving techniques are strongly needed. In this paper we employ frequent-pattern tree (FP-tree) structure storing compressed crucial information about frequent patterns and develop an efficient and secure FP-treebased mining method. We show that our protocol is collusion resistant which means that even if all dishonest respondents collude with a dishonest data minerin an attempt to learn the associations between honest respondents and their responses they will be unable to do so. Key words association rule mining privacy-preserving data mining FP-tree attributes-based encryption | |||||||
論文抄録(英) | ||||||||
内容記述タイプ | Other | |||||||
内容記述 | Assocaition Rules Mining is a frequently used technique which finds interesting associations and correlation relationships among large set of data items that occur frequently together in varieties of social and bussiness area. For the coopertional distributed assocaition rules mining, privacy-preserving techniques are strongly needed. In this paper, we employ frequent-pattern tree (FP-tree) structure storing compressed, crucial information about frequent patterns, and develop an efficient and secure FP-treebased mining method. We show that our protocol is collusion resistant, which means that even if all dishonest respondents collude with a dishonest data minerin an attempt to learn the associations between honest respondents and their responses, they will be unable to do so. Key words association rule mining, privacy-preserving data mining, FP-tree, attributes-based encryption | |||||||
書誌レコードID | ||||||||
収録物識別子タイプ | NCID | |||||||
収録物識別子 | AA11235941 | |||||||
書誌情報 |
情報処理学会研究報告コンピュータセキュリティ(CSEC) 巻 2007, 号 71(2007-CSEC-038), p. 133-138, 発行日 2007-07-19 |
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Notice | ||||||||
SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc. | ||||||||
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言語 | ja | |||||||
出版者 | 情報処理学会 |