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rho-uncertainty: Inference-Proof Transaction Anonymization

Summary: rho-uncertainty is the first inference-proof privacy notion for transaction anonymization, guarding sensitive-item associations regardless of adversary knowledge without falsifying data. A hybrid generalization-suppression scheme achieves this with non-trivial information loss and outperforms perturbation baselines. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
10147
Venue
VLDB
Year
2010
Pagerank
5.4828795e-05
Overall Rank
5,483 | 61.86%
DOI
-

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 4 of 4 citing papers.

Rank Citing Paper Year Venue Pagerank
1,567 PrivBasis: Frequent Itemset Mining with Differential Privacy 2012 VLDB 0.0001133268
2,685 On Differentially Private Frequent Itemset Mining 2013 VLDB 8.3070708e-05
3,097 Publishing Set-Valued Data via Differential Privacy 2011 VLDB 7.5647028e-05
8,930 Privacy Preservation by Disassociation 2012 VLDB 4.427232e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 cited papers.

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

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