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Revealing Information while Preserving Privacy

Summary: Model DB as an n-bit vector and give a polynomial-time reconstruction algorithm that recovers the data from noisy subset-sum answers, showing privacy is violated unless noise is Ω(√n). Tightness: exhibit access schemes with Õ(√n) noise; for time-T adversaries required noise ≈√T. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1292
Venue
PODS
Year
2003
Pagerank
0.0004241101
Overall Rank
136 | 99.06%
DOI
-

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

Rank Cited Paper Year Venue Pagerank
40 Privacy-Preserving Data Mining 2000 SIGMOD 0.00074232718
89 Statistical Databases: Characteristics, Problems, and Some Solutions 1982 VLDB 0.0005230007
147 On the Design and Quantification of Privacy Preserving Data Mining Algorithms 2001 PODS 0.00041235556
564 An Analytic Approach to Statistical Databases 1983 VLDB 0.00020017414
1,506 Auditing Boolean Attributes 2000 PODS 0.00011618118
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