AI RESEARCH
Inferring Sensitive Attributes from Knowledge Graph Embeddings: Attack and Defense Strategies
arXiv CS.LG
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ArXi:2605.19644v1 Announce Type: cross Knowledge Graphs (KGs) are a powerful representation of linked data, offering flexibility, semantic richness, and for knowledge enrichment and reasoning. They help data owners organize and exploit heterogeneous data to provide insightful services (e.g., recommendations), yet real-world KGs are often incomplete, hiding true facts or missing valuable insights. Knowledge graph embedding techniques are commonly used to infer valuable missing information.