PRIVEE: A Visual Analytic Workflow for Proactive Privacy Risk Inspection of Open Data. (arXiv:2208.06481v1 [cs.CR])

Open data sets that contain personal information are susceptible to
adversarial attacks even when anonymized. By performing low-cost joins on
multiple datasets with shared attributes, malicious users of open data portals
might get access to information that violates individuals' privacy. However,
open data sets are primarily published using a release-and-forget model,
whereby data owners and custodians have little to no cognizance of these
privacy risks. We address this critical gap by developing a visual analytic
solution that enables data defenders …

data privacy proactive risk