2013/04/29 by Latanya Sweeney, Sweeney, Latanya, Akua Abu +3 · 2 citations
Computer Science · Social Sciences · #Climate Change Communication and Perception #Computers and Society (cs.CY) #FOS: Computer and information sciences #H.1.2 #H.2.0 #H.2.7 #H.3.5 #J.3 #K.4.1 #K.6.5 #cs.CY
paper · pdf · doi:10.48550/arxiv.1304.7605
4 pages
arxiv created 2013/04/29 · openalex publication_date 2013/04/29 · arxiv updated 2013/04/30 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
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.