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Personalized Privacy Protection in Social Networks

Summary: Introduces personalized social-network privacy against attackers with heterogeneous background knowledge, defining three protection levels. Combines label generalization with structural perturbations (noisy edges/nodes), trading privacy requirements against utility and validating the framework experimentally. (summarized by gpt-5.6-luna on Jul 24 2026)

Paper ID
10404
Venue
VLDB
Year
2011
Pagerank
5.4119882e-05
Overall Rank
8,545 | 41.38%
DOI
10.14778/1920841.1920866

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@article{yuan_vldb11,
        title = {{Personalized Privacy Protection in Social Networks}},
        author = {Yuan, Mingxuan and Chen, Lei and Yu, Philip S.},
        journal = {PVLDB},
        series = {{VLDB} '11},
        volume = {4},
        number = {2},
        pages = {141--152},
        doi = {10.14778/1920841.1920866},
        url = {https://doi.org/10.14778/1920841.1920866},
        year = {2011}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
4,029 Differential Privacy in Telco Big Data Platform 2015 VLDB 6.946445e-05
11,203 Personalized Truncation for Personalized Privacy 2024 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

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