Researchers at Carnegie Mellon University in US have sounded an alarm on the nation's Social Security numbering system. They say the system has left millions of citizens vulnerable to privacy breaches.
The researchers used statistical techniques to predict Social Security Numbers based solely on an individual's date and birth place. The researchers, Alessandro Acquisti, an associate professor of information technology and public policy, and Ralph Gross, a postdoctoral researcher, point to a range of implications from the research including the possibility to routinely reconstruct sensitive personal information from the type of online postings commonly seen on social networking sites and other public sources.
According to analysts, the findings published in The Proceedings of the National Academy of Sciences, are further evidence that privacy safeguards from the era prior to the appearance of powerful computers and ubiquitous networks are increasingly failing to safeguard the security of personal digital information.
Identity theft, which has now assumed global dimensions, has emerged as a major threat with the phenomenal growth of the internet. Social Security Numbers are used widely for identification and authentication and are sold both by digital information aggregators and on blackmarkets set up for the purpose of identity theft.
The authors say the predictability of Social Security numbers is ''an unexpected consequence of the interaction between multiple data sources, trends in information exposure and antifraud policy initiatives with unintended effects.''
The researchers analysed Social Security numbers of people who have died to detect statistical patterns in the assignment of numbers and from these they were able to predict a range of values likely to include a living person's Social Security number. Birth data can be inferred from a number of sources including data brokers, voter registration, on-line white pages and social-networking profiles the researchers say.