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Privacy: From Database Reconstruction to Legal Theorems

Summary: Formalizes legal privacy standards as provable "legal theorems" to bridge legal and technical gaps, mapping concepts like GDPR "singling out" into precise mathematical definitions. Proves whether mechanisms (k‑anonymity, differential privacy) and reconstruction attacks meet those legal notions. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
1833
Venue
PODS
Year
2021
Pagerank
4.1945683e-05
Overall Rank
11,444 | 20.39%
DOI
10.1145/3452021.3458816

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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
136 Revealing Information while Preserving Privacy 2003 PODS 0.0004241101
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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