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Efficient Heuristic Algorithm for Privacy-Optimized Randomized Response
https://ipsj.ixsq.nii.ac.jp/records/234043
https://ipsj.ixsq.nii.ac.jp/records/23404365f821ff-50ca-453c-925f-e68957c59b69
| 名前 / ファイル | ライセンス | アクション |
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IPSJ-AL24198004.pdf (1.1 MB)
2026年5月1日からダウンロード可能です。
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Copyright (c) 2024 by the Information Processing Society of Japan
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| 非会員：¥660, IPSJ:学会員：¥330, AL:会員：¥0, DLIB:会員：¥0 | ||
| Item type | SIG Technical Reports(1) | |||||||||
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| 公開日 | 2024-05-01 | |||||||||
| タイトル | ||||||||||
| タイトル | Efficient Heuristic Algorithm for Privacy-Optimized Randomized Response | |||||||||
| タイトル | ||||||||||
| 言語 | en | |||||||||
| タイトル | Efficient Heuristic Algorithm for Privacy-Optimized Randomized Response | |||||||||
| 言語 | ||||||||||
| 言語 | eng | |||||||||
| 資源タイプ | ||||||||||
| 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 | ||||||||||
| The University of Tokyo | ||||||||||
| 著者所属 | ||||||||||
| The University of Tokyo | ||||||||||
| 著者所属(英) | ||||||||||
| en | ||||||||||
| The University of Tokyo | ||||||||||
| 著者所属(英) | ||||||||||
| en | ||||||||||
| The University of Tokyo | ||||||||||
| 著者名 |
Akito, Yamamoto
× Akito, Yamamoto
× Tetsuo, Shibuya
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| 著者名(英) |
Akito, Yamamoto
× Akito, Yamamoto
× Tetsuo, Shibuya
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| 論文抄録 | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | With the increasing amount of data in society, privacy concerns in data sharing have become widely recognized. Particularly, it is essential to protect personal attribute information. Although various differentially private methods based on randomized response have been proposed, there is a lack of studies on the mechanism for sharing multi-attribute data. The existing randomized response for this purpose uses the Kronecker product to perturb each attribute information in turn according to the respective privacy level but achieves only a weak privacy level for the entire dataset. Therefore, we first describe a privacy-optimized randomized response that guarantees the strongest privacy in sharing multi-attribute data. Thereafter, we present an efficient heuristic algorithm for constructing a near-optimal mechanism. The time complexity of our algorithm is O(k2), where k is the number of attributes. The experimental results demonstrate the utility of our methods. | |||||||||
| 論文抄録(英) | ||||||||||
| 内容記述タイプ | Other | |||||||||
| 内容記述 | With the increasing amount of data in society, privacy concerns in data sharing have become widely recognized. Particularly, it is essential to protect personal attribute information. Although various differentially private methods based on randomized response have been proposed, there is a lack of studies on the mechanism for sharing multi-attribute data. The existing randomized response for this purpose uses the Kronecker product to perturb each attribute information in turn according to the respective privacy level but achieves only a weak privacy level for the entire dataset. Therefore, we first describe a privacy-optimized randomized response that guarantees the strongest privacy in sharing multi-attribute data. Thereafter, we present an efficient heuristic algorithm for constructing a near-optimal mechanism. The time complexity of our algorithm is O(k2), where k is the number of attributes. The experimental results demonstrate the utility of our methods. | |||||||||
| 書誌レコードID | ||||||||||
| 収録物識別子タイプ | NCID | |||||||||
| 収録物識別子 | AN1009593X | |||||||||
| 書誌情報 |
研究報告アルゴリズム（AL） 巻 2024-AL-198, 号 4, p. 1-8, 発行日 2024-05-01 |
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| ISSN | ||||||||||
| 収録物識別子タイプ | ISSN | |||||||||
| 収録物識別子 | 2188-8566 | |||||||||
| Notice | ||||||||||
| SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc. | ||||||||||
| 出版者 | ||||||||||
| 言語 | ja | |||||||||
| 出版者 | 情報処理学会 | |||||||||
