Identifying Participants in the Personal Genome Project by Name (A Re-identification Experiment)

We linked names and contact information to publicly available profiles in the Personal Genome Project. These profiles contain medical and genomic information, including details about medications, procedures and diseases, and demographic information, such as date of birth, gender, and postal code. By linking demographics to public records such as voter lists, and mining for names hidden in attached documents, we correctly identified 84 to 97 percent of the profiles for which we provided names. Our ability to learn their names is based on their demographics, not their DNA, thereby revisiting an old vulnerability that could be easily thwarted with minimal loss of research value. So, we propose technical remedies for people to learn about their demographics to make better decisions.

• Publication year

  2013

• Venue

  arXiv.org

• Publication date

  2013-04-29

• Fields of study

  Biology, Medicine, Computer Science

• Identifiers
  DOI 10.2139/SSRN.2257732arXiv 1304.7605
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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