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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/10119/10333
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| タイトル: | A Distributed Solution for Privacy Preserving Outlier Detection |
| 著者: | Luong, The Dung
Ho, Tu Bao |
| キーワード: | Privacy Preserving Outlier Detection
Distributed Solution |
| 発行日: | 2011-10-14 |
| 出版者: | Institute of Electrical and Electronics Engineers (IEEE) |
| 誌名: | 2011 Third International Conference on Knowledge and Systems Engineering (KSE) |
| 開始ページ: | 26 |
| 終了ページ: | 31 |
| DOI: | 10.1109/KSE.2011.13 |
| 抄録: | In this paper, we study some parties - each has a private data set - want to conduct the outlier detection on their joint data set, but none of them want to disclose its private data to the other parties. We propose a linear transformation technique to design protocols of secure multivariate outlier detection in both horizontally and vertically distributed data models. While different from the most of previous techniques in a privacy preserving fashion for distance-based outliers detection, our focusis the technique in statistics for detecting outliers. |
| Rights: | Copyright (C) 2011 IEEE. Reprinted from 2011 Third International Conference on Knowledge and Systems Engineering (KSE), 2011, 26-31. This material is posted here with permission of the IEEE. Such permission of the IEEE does not in any way imply IEEE endorsement of any of JAIST's products or services. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it. |
| URI: | http://hdl.handle.net/10119/10333 |
| 資料タイプ: | author |
| 出現コレクション: | a11-1. 会議発表論文 (Conference Papers)
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このアイテムのファイル:
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記述 |
サイズ | 形式 |
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| 17332.pdf | | 89Kb | Adobe PDF | 見る/開く |
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