Resilience of clinical text de-identified with “hiding in plain sight” to hostile reidentification attacks by human readers | Zendy

David Carrell | Zendy; Bradley Malin | Zendy; David Cronkite | Zendy; John Aberdeen | Zendy; Cheryl Clark | Zendy; Muqun Li | Zendy; Dikshya Bastakoty | Zendy; Steve Nyemba | Zendy; Lynette Hirschman | Zendy

Open Access

Resilience of clinical text de-identified with “hiding in plain sight” to hostile reidentification attacks by human readers

Author(s) -

David Carrell,

Bradley Malin,

David Cronkite,

John Aberdeen,

Cheryl Clark,

Muqun Li,

Dikshya Bastakoty,

Steve Nyemba,

Lynette Hirschman

Publication year - 2020

Publication title -

journal of the american medical informatics association

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.614

H-Index - 150

eISSN - 1527-974X

pISSN - 1067-5027

DOI - 10.1093/jamia/ocaa095

Subject(s) - resilience (materials science) , sight , computer science , astronomy , thermodynamics , physics

Effective, scalable de-identification of personally identifying information (PII) for information-rich clinical text is critical to support secondary use, but no method is 100% effective. The hiding-in-plain-sight (HIPS) approach attempts to solve this "residual PII problem." HIPS replaces PII tagged by a de-identification system with realistic but fictitious (resynthesized) content, making it harder to detect remaining unredacted PII.

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