Team for Research in
Ubiquitous Secure Technology

Citation
Alessandro Acquisti. "Predicting Social Security Numbers from Public Data". Proceedings of the National Academy of Science, 2009; http://www.pnas.org/content/early/2009/07/02/0904891106.full.pdf+html.

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.

Electronic downloads

• http://www.pnas.org/content/early/2009/07/02/0904891106.full.pdf+html

• HTML

  Alessandro Acquisti. <a
  href="http://www.truststc.org/pubs/671.html"
  >Predicting Social Security Numbers from Public
  Data</a>, <i>Proceedings of the National Academy
  of Science</i>,  2009;
  http://www.pnas.org/content/early/2009/07/02/0904891106.full.pdf+html.

• Plain text

  Alessandro Acquisti. "Predicting Social Security
  Numbers from Public Data". <i>Proceedings of the
  National Academy of Science</i>,  2009;
  http://www.pnas.org/content/early/2009/07/02/0904891106.full.pdf+html.

• BibTeX

  @article{Acquisti09_PredictingSocialSecurityNumbersFromPublicData,
      author = {Alessandro Acquisti},
      title = {Predicting Social Security Numbers from Public Data},
      journal = {Proceedings of the National Academy of Science},
      year = {2009},
      note = {http://www.pnas.org/content/early/2009/07/02/0904891106.full.pdf+html},
      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. },
      URL = {http://www.truststc.org/pubs/671.html}
  }
  

Posted by Alessandro Acquisti on 29 Mar 2010.
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