VeriX-Anon: Multi-Layered Framework for Verifiable Outsourced Data Anonymization
VeriX-Anon is a multi-layered verification framework for outsourced target-driven k-anonymization, combining deterministic, probabilistic, and explainable AI-based mechanisms. In evaluations across seven datasets and four cloud profiles, it detected 25 to 27 out of 28 adversarial deviations with no false alarms, and client-side verification completed in under one second for datasets with one million rows. The framework addresses a gap in verifying that privacy-sensitive data transformations are faithfully executed by cloud providers.
Why it matters: VeriX-Anon offers a practical, mathematically grounded method for data owners to verify the integrity of outsourced privacy-preserving data transformations, addressing a key trust issue in cloud-based data processing.
Full story at: arXiv Cryptography and Security ↗