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Personalized Privacy Protection in Social Networks

Summary: Personalized privacy framework for social graphs with multi-level attacker knowledge; targets heterogeneous user privacy needs. Combines label generalization with structural protection (noise edges/nodes) to tailor per-user safeguards; experiments show utility-privacy trade-offs. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10213
Venue
VLDB
Year
2011
Pagerank
4.5435639e-05
Overall Rank
8,309 | 42.20%
DOI
-

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Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank Citing Paper Year Venue Pagerank
4,039 Differential Privacy in Telco Big Data Platform 2015 VLDB 6.5075964e-05
10,992 Personalized Truncation for Personalized Privacy 2024 SIGMOD 4.1945683e-05
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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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