Post #1331542
2026-03-01 21:06 UTC
@sigismundninja “Compared to classical deanonymization work (e.g., on the Netflix prize) that
required structured data , our approach works directly on raw user content across arbitrary platforms”
Replies (1)
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@UlrikeHahn@fediscience.org 2026-03-01 21:09
@sigismundninja “Our contributions. We demonstrate that LLMs funda- mentally change the picture, enabling fully automated deanonymization attacks that operate on unstructured text at scale. We show this by phrasing deanonymization as a matching problem and showing LLMs can perform all steps needed to match accounts: extract identity-relevant signals from arbitrary text, efficiently search over millions of candidate profiles, and reason about whether two accounts belong to the same person. We show that the practical obscurity that has long protected pseudonymous users (the assumption that deanonymization, while theoretically possible, is too costly to execute broadly) no longer holds”