Demo Data from VLDB 2026 / reviewers in the wild / expert
Mary K. Righi
dblp:417/5162
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2025
0000-0001-8897-419XORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Security and privacy · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
1 paper |
Privacy and data protection · 100% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Privacy and data protection
anonymization |
0.9 | 1 | 2025 | Exposing Privacy Risks in Anonymizing Clinical Data: Combinatorial Refinement Attacks on k-Anonymity Without Auxiliary Information · CCS 2025 |
Privacy and data protection › anonymization
k-anonymity |
0.9 | 1 | 2025 | Exposing Privacy Risks in Anonymizing Clinical Data: Combinatorial Refinement Attacks on k-Anonymity Without Auxiliary Information · CCS 2025 |
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Exposing Privacy Risks in Anonymizing Clinical Data: Combinatorial Refinement Attacks on k-Anonymity Without Auxiliary InformationabstractDespite longstanding criticism from the privacy community, k-anonymity remains a widely used standard for data anonymization, mainly due to its simplicity, regulatory alignment, and preservation of data utility. However, non-experts often defend k-anonymity on the grounds that, in the absence of auxiliary information, no known attacks can compromise its protections. Somiya Chhillar, Mary K. Righi, Rebecca E. Sutter, Evgenios M. Kornaropoulos |
CCS | 2 |