HPGA: An efficient hierarchical algorithm for personalized graph data anonymization

This academic paper describes HPGA, an algorithm designed to anonymize graph data (networks of connected nodes and edges) while preserving personalized information. The research, published in December 2026, addresses the challenge of protecting privacy in graph-structured datasets, which are commonly used in social networks and recommendation systems.