| Item type |
SIG Technical Reports(1) |
| 公開日 |
2024-07-15 |
| タイトル |
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|
タイトル |
Utility Analysis of Differentially Private Anonymized Data Based on Random Sampling |
| タイトル |
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言語 |
en |
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タイトル |
Utility Analysis of Differentially Private Anonymized Data Based on Random Sampling |
| 言語 |
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|
言語 |
eng |
| キーワード |
|
|
主題Scheme |
Other |
|
主題 |
IPSJ-CSEC |
| 資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_18gh |
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資源タイプ |
technical report |
| 著者所属 |
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Chuo University, Graduate School of Economics |
| 著者所属 |
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SECOM CO., LTD. |
| 著者所属 |
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Raksu Co Ltd. |
| 著者所属 |
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The Institute of Statistical Mathematics, Department of Interdisciplinary Statistical Mathematics |
| 著者所属(英) |
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en |
|
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Chuo University, Graduate School of Economics |
| 著者所属(英) |
|
|
|
en |
|
|
SECOM CO., LTD. |
| 著者所属(英) |
|
|
|
en |
|
|
Raksu Co Ltd. |
| 著者所属(英) |
|
|
|
en |
|
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The Institute of Statistical Mathematics, Department of Interdisciplinary Statistical Mathematics |
| 著者名 |
Takumi, Sugiyama
Hiroto, Oosugi
Io, Yamanaka
Kazuhiro, Minami
|
| 著者名(英) |
Takumi, Sugiyama
Hiroto, Oosugi
Io, Yamanaka
Kazuhiro, Minami
|
| 論文抄録 |
|
|
内容記述タイプ |
Other |
|
内容記述 |
It is possible to produce differentially private k-anonymized data based on the method of random sampling followed by full-domain generalization for k-anonymization. We previously evaluate the performance of that method, which is implemented as the SafePub algorithm in the ARX anonymization tool. However, since the SafePub algorithm chooses to use the maximum sampling rate that satisfies the requirements for differential privacy, we observe paradoxical results of diminishing data utility as we increase the privacy budget for differential privacy. In this paper, we, therefore, conduct preliminary experiments to explore the parameter space for privacy budget and sampling rate by setting the sampling rates explicitly by modifying the implementation of ARX. Our initial results show the possibility of improving the utility of anonymized data by properly setting the sampling rate below its maximum value. |
| 論文抄録(英) |
|
|
内容記述タイプ |
Other |
|
内容記述 |
It is possible to produce differentially private k-anonymized data based on the method of random sampling followed by full-domain generalization for k-anonymization. We previously evaluate the performance of that method, which is implemented as the SafePub algorithm in the ARX anonymization tool. However, since the SafePub algorithm chooses to use the maximum sampling rate that satisfies the requirements for differential privacy, we observe paradoxical results of diminishing data utility as we increase the privacy budget for differential privacy. In this paper, we, therefore, conduct preliminary experiments to explore the parameter space for privacy budget and sampling rate by setting the sampling rates explicitly by modifying the implementation of ARX. Our initial results show the possibility of improving the utility of anonymized data by properly setting the sampling rate below its maximum value. |
| 書誌レコードID |
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収録物識別子タイプ |
NCID |
|
収録物識別子 |
AA12628305 |
| 書誌情報 |
研究報告セキュリティ心理学とトラスト（SPT）
巻 2024-SPT-56,
号 2,
p. 1-6,
発行日 2024-07-15
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| ISSN |
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収録物識別子タイプ |
ISSN |
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収録物識別子 |
2188-8671 |
| Notice |
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SIG Technical Reports are nonrefereed and hence may later appear in any journals, conferences, symposia, etc. |
| 出版者 |
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言語 |
ja |
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出版者 |
情報処理学会 |
IPSJ-SPT24056002.pdf (997.9 kB)
