Item type |
Symposium(1) |
公開日 |
2016-10-04 |
タイトル |
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タイトル |
Privacy-Preserving Trajectory Data Publishing from Adversary with Limited Information |
タイトル |
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言語 |
en |
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タイトル |
Privacy-Preserving Trajectory Data Publishing from Adversary with Limited Information |
言語 |
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言語 |
eng |
キーワード |
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主題Scheme |
Other |
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主題 |
trajectory,privacy,data publication |
資源タイプ |
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資源タイプ識別子 |
http://purl.org/coar/resource_type/c_5794 |
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資源タイプ |
conference paper |
著者所属 |
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Graduate School of Information Science and Technology, The University of Tokyo |
著者所属 |
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Graduate School of Information Science and Technology, The University of Tokyo |
著者所属 |
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Graduate School of Information Science and Technology, The University of Tokyo |
著者所属(英) |
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en |
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Graduate School of Information Science and Technology, The University of Tokyo |
著者所属(英) |
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en |
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Graduate School of Information Science and Technology, The University of Tokyo |
著者所属(英) |
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en |
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Graduate School of Information Science and Technology, The University of Tokyo |
著者名 |
Seongun, Choi
Toshiro, Hikita
Rie, Shigetomi Yamaguchi
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著者名(英) |
Seongun, Choi
Toshiro, Hikita
Rie, Shigetomi Yamaguchi
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論文抄録(英) |
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内容記述タイプ |
Other |
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内容記述 |
Privacy issues obstacles data publication because sanitizing data to satisfy privacy notions eventually lowers the data usefulness. For trajectory data, it is challenging to remove privacy threat and to retain data usefulness at the same time because of its high dimensionality and sequentiality. Additionally, anonymizing trajectory data has two conflicting goals of k-anonymity and l-diversity. Many researches had limited focus on k-anonymity for trajectory data, in this paper, we consider both k-anonymity and l-diversity by supposing a weak adversary who has limited information of pre-determined locations. We sanitize data not to allow the adversary to know victim's private doublets. |
書誌レコードID |
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識別子タイプ |
NCID |
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関連識別子 |
ISSN 1882-0840 |
書誌情報 |
コンピュータセキュリティシンポジウム2016論文集
巻 2016,
号 2,
p. 914-920,
発行日 2016-10-04
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出版者 |
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言語 |
ja |
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出版者 |
情報処理学会 |