Predicting Social Security Numbers from Public Data
Proceedings of the National Academy of Sciences, 106(27):10975-10980 07 Jul 2009 http://doi.org/10.1073/pnas.0904891106
Posted: 6 Jan 2019 Last revised: 18 Nov 2021
Date Written: 2009
Abstract
Information about an individual’s place and date of birth can be exploited to predict his or her Social Security number (SSN). Using only publicly available information, we observed a correlation between individuals’ SSNs and their birth data and found that for younger cohorts the correlation allows statistical inference of private SSNs. The inferences are made possible by the public availability of the Social Security Administration’s Death Master File and the widespread accessibility of personal information from multiple sources, such as data brokers or profiles on social networking sites. Our results highlight the unexpected privacy consequences of the complex interactions among multiple data sources in modern information economies and quantify privacy risks associated with information revelation in public forums.
Keywords: identity theft, online social networks, privacy, statistical reidentification
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