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

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📝 Original Info

  • Title: Identifying Participants in the Personal Genome Project by Name (A Re-identification Experiment)
  • ArXiv ID: 1304.7605
  • Date: 2013-04-30
  • Authors: Researchers from original ArXiv paper

📝 Abstract

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.

💡 Deep Analysis

Deep Dive into 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.

📄 Full Content

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.

Reference

This content is AI-processed based on ArXiv data.

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