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From the Cover: Predicting Social Security numbers from public data
Authors:Alessandro Acquisti  Ralph Gross
Affiliation:Carnegie Mellon University, Pittsburgh, PA 15213
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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