| アイテムタイプ |
学術雑誌論文 / Journal Article(1) |
| 公開日 |
2025-12-19 |
| タイトル |
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タイトル |
D2-PSD: Dynamic Differentially-Private Spatial Decomposition in Collaboration with Edge Server |
| 言語 |
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言語 |
eng |
| キーワード |
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主題Scheme |
Other |
|
主題 |
Local differential privacy |
| キーワード |
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主題Scheme |
Other |
|
主題 |
private spatial decomposition |
| キーワード |
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主題Scheme |
Other |
|
主題 |
spatio-temporal data |
| キーワード |
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主題Scheme |
Other |
|
主題 |
geospatial clustering |
| キーワード |
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主題Scheme |
Other |
|
主題 |
edge computing |
| 資源タイプ |
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資源タイプ |
journal article |
| アクセス権 |
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アクセス権 |
open access |
| 著者 |
笹田, 大翔
妙中, 雄三
門林, 雄基
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| 抄録 |
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内容記述タイプ |
Abstract |
|
内容記述 |
Spatio-temporal data possess intrinsic values, reflecting the spatial and temporal features of people’s behaviors. Due to the sensitive nature of this data (e.g., workplace, residence, school locations), privacy protection is essential when collecting spatio-temporal data. Local Differential Privacy (LDP) protocol has gained attention as a method for protecting privacy on data-collecting devices. LDP protocol can make each data indistinguishable but inevitably destroys spatial/temporal characteristics as well. In this paper, we propose a novel method enabling LDP protocol to preserve spatial/temporal trends on privacy protection. If we collect data from users with similar behavior, it is difficult to uniquely identify users from the beginning. In short, processing privacy protection for each user with similar behavior allow us to minimize the removal of intrinsic values by LDP protocol. Our method, termed Dynamic Differentially-Private Spatial Decomposition (D2-PSD), dynamically adjusts and controls the strength of privacy protection (privacy budget) for each group of users exhibiting similar spatial and temporal trends. This allows users to be indistinguishable from each other within a group while preserving spatial and temporal trends across groups. All groups will have a different privacy budget, but the sum of the entire group keeps a constant privacy budget. Even if group with different protection strengths are mixed, privacy is protected for the sum of the group, and our proposed method can always guarantee a constant protection strength. Experimental results demonstrate that our method retains the intrinsic spatial and temporal trends in spatio-temporal data while maintaining robust privacy protection across the entire dataset, thanks to the D2-PSD approach. Specifically, in the most similar groups, D2-PSD reduced the MAE by up to 75% compared to standard LDP, while maintaining an equivalent strength of privacy protection. |
| 書誌情報 |
en : IEEE Access
巻 12,
p. 156307-156326,
ページ数 20,
発行日 2024-10-24
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| 出版者 |
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出版者 |
IEEE |
| ISSN |
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収録物識別子タイプ |
EISSN |
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収録物識別子 |
2169-3536 |
| 出版者版DOI |
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関連タイプ |
isIdenticalTo |
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識別子タイプ |
DOI |
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関連識別子 |
https://doi.org/10.1109/ACCESS.2024.3485610 |
| 出版者版URI |
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関連タイプ |
isIdenticalTo |
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|
識別子タイプ |
URI |
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|
関連識別子 |
https://ieeexplore.ieee.org/document/10734200 |
| 権利 |
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|
権利情報Resource |
https://creativecommons.org/licenses/by-nc-nd/4.0/ |
|
権利情報 |
© 2024 The Authors. This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/ |
| 著者版フラグ |
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出版タイプ |
VoR |
| 助成情報 |
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助成機関名 |
Japan Society for the Promotion of Science (JSPS) |
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研究課題番号 |
JP22J23910 |
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研究課題番号URI |
https://kaken.nii.ac.jp/ja/grant/KAKENHI-PROJECT-22KJ2294/ |
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研究課題名 |
時空間データの特性に適応する実践的プライバシ保護技術に関する研究 |
| 助成情報 |
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助成機関名 |
Japan Society for the Promotion of Science (JSPS) |
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研究課題番号 |
JP24K03045 |
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研究課題番号URI |
https://kaken.nii.ac.jp/ja/grant/KAKENHI-PROJECT-24K03045/ |
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研究課題名 |
データセントリックな信頼志向データ流通管理の研究 |
| 助成情報 |
|
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助成機関名 |
Daiichi-Sankyo |
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|
研究課題名 |
‘‘Habataku’’ Support Program for the Next Generation of Researchers |
| 助成情報 |
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助成機関名 |
Nara Institute Science and Technology |
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研究課題名 |
Senju Monju Project |
fulltext (2.4 MB)
