Private Graph Analysis

Private Graph Analysis is a methodological framework within differential privacy that enables the extraction of statistical insights from graph-structured data while formally guaranteeing individual privacy through rigorous noise calibration mechanisms.

19

Publications

1.3K

Citations

58

Authors

26

Institutions

Publications per year

2017–2026

9

Authors

58

  1. AS
    Adam Smith

    Pennsylvania State University, United States

    2 publications · 277 citations

    2

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  2. SR
    Sofya Raskhodnikova

    Pennsylvania State University, United States

    2 publications · 277 citations

    2

    h-index

  3. VK
    Vishesh Karwa

    Pennsylvania State University, United States

    2 publications · 277 citations

    2

    h-index

  4. GY
    Grigory Yaroslavtsev

    Pennsylvania State University, United States

    2 publications · 277 citations

    2

    h-index

  5. XX
    Xiaokui Xiao

    Nanyang Technological University, Singapore

    2 publications · 154 citations

    2

    h-index

1–5 of 58

Venues

  1. Proceedings of the VLDB Endowment

    PVLDB · 1 publications · 194 citations

    1

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  2. World Wide Web

    1 publications · 51 citations

    1

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  3. 1

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  4. arXiv (Cornell University)

    Repository · 1 publications · 13 citations

    1

    h-index

  5. IEEE Transactions on Knowledge and Data Engineering

    TKDE · 1 publications · 45 citations

    1

    h-index

1–5