Towards Identity Anonymization on Graphs
Summary: Defines k-degree anonymity: every node has at least k−1 others with the same degree, enabling privacy against degree-based re-identification. Presents minimal-graph-modification algorithms to reach a closest k-degree anonymous graph, leveraging degree-sequence realizability; validated on synthetic and real networks. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Kun Liu
- 2. Evimaria Terzi
Incoming Citations (Sorted by Pagerank)
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Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 225 | Generalizing Data to Provide Anonymity when Disclosing Information | 1998 | PODS | 0.00032707646 |
| 304 | On the Complexity of Optimal K-Anonymity | 2004 | PODS | 0.00028290121 |
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