Private Triangle Counting for Degeneracy-bounded Graphs

• Item type: SIG Technical Reports(1)
• 公開日: 2024-03-14
• タイトル: Private Triangle Counting for Degeneracy-bounded Graphs
• タイトル / 言語: en
• タイトル: Private Triangle Counting for Degeneracy-bounded Graphs
• 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: The University of Tokyo
• 著者所属(英): en
• 著者所属(英): The University of Tokyo
• 著者所属(英): en
• 著者所属(英): The University of Tokyo
• 著者所属(英): en
• 著者所属(英): The University of Tokyo
• 著者名: Quentin, Hillebrand; Vorapong, Suppakitpaisarn; Tetsuo, Shibuya
• 著者名(英): Quentin, Hillebrand; Vorapong, Suppakitpaisarn; Tetsuo, Shibuya
• 論文抄録 / 内容記述タイプ: Other
• 論文抄録 / 内容記述: This article introduces a new triangle counting algorithm under the framework of edge local differential privacy leveraging the degeneracy-bounded nature of real-world graphs. We describe a pre-processing step that performs a re-ordering of the vertices according to their degrees. Despite its small budget usage, this ordering effectively reduces the occurrence of some specific patterns in the graph. In turn, the diminished number of those patterns enable our triangle counting algorithm to minimize its error on the estimation. This results in the error of our triangle counting scaling as a function of the degeneracy unlike state of the art algorithms for which it was scaling with the maximal degree, effectively increasing the accuracy in practice.
• 論文抄録(英) / 内容記述タイプ: Other
• 論文抄録(英) / 内容記述: This article introduces a new triangle counting algorithm under the framework of edge local differential privacy leveraging the degeneracy-bounded nature of real-world graphs. We describe a pre-processing step that performs a re-ordering of the vertices according to their degrees. Despite its small budget usage, this ordering effectively reduces the occurrence of some specific patterns in the graph. In turn, the diminished number of those patterns enable our triangle counting algorithm to minimize its error on the estimation. This results in the error of our triangle counting scaling as a function of the degeneracy unlike state of the art algorithms for which it was scaling with the maximal degree, effectively increasing the accuracy in practice.
• 書誌レコードID / 収録物識別子タイプ: NCID
• 書誌レコードID / 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-197, 号 1, p. 1-7, 発行日 2024-03-14
• ISSN / 収録物識別子タイプ: ISSN
• 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