Map collection, inference, storage, retrieval, sharing, logging, and deletion across graph edges. Threats include overcollection, linkage, memorization, unauthorized inference, and retention drift.

Privacy Threat Modeling Follows Data Paths

Federated designs keep data within organizational or device boundaries while sharing updates, queries, or aggregate evidence. Metadata leakage, poisoning, and unequal participation remain risks.

Federated Agent Graphs Coordinate Without Centralizing Raw Data

In this situation—personalizing a tutor from chat, assessments, and accessibility data—which choice best applies “Privacy Threat Modeling Follows Data Paths”?

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