Measuring Re-identification Risk

Summary: New framework to measure re-identification risk of compact user representations via hypothesis-testing bounds. Applied to real-world settings (Chrome Topics API) with attack algorithms to estimate risk, delivering an interpretable data-management metric. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 6652
Venue: SIGMOD
Year: 2023
Pagerank: 4.5435639e-05
Overall Rank: 8,283 | 42.38%
DOI: 10.1145/3589294

Incoming Non-self Citations Over Time

Authors

Incoming Citations (Sorted by Pagerank)

Showing 1 of 1 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
10,262	Understanding Disclosure Risk in Differential Privacy with Applications to Noise Calibration and Auditing	2026	VLDB	4.1945683e-05

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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
177	Limiting Privacy Breaches in Privacy Preserving Data Mining	2003	PODS	0.0003788711
304	On the Complexity of Optimal K-Anonymity	2004	PODS	0.00028290121
2,806	CryptEpsilon: Crypto-Assisted Differential Privacy on Untrusted Servers	2020	SIGMOD	8.0911177e-05
2,899	Privacy at Scale: Local Differential Privacy in Practice	2018	SIGMOD	7.9443198e-05
5,687	Differential Privacy in the Wild: A Tutorial on Current Practices & Open Challenges	2017	SIGMOD	5.3706593e-05
5,872	Differential Privacy and the US Census	2019	PODS	5.2937278e-05

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