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Social Security Numbers are predictable, Carnegie Mellon researchers find

Algorithm created based on SSNs of the deceased

By Alpha Doggs on Tue, 07/07/09 - 10:26am.
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Carnegie Mellon University researchers have created an algorithm that can predict Social Security Numbers based on publicly available information from government sources, social networks and other data repositories.

"In a world of wired consumers, it is possible to combine information from multiple sources to infer data that is more personal and sensitive than any single piece of original information alone," said Project lead Alessandro Acquisti, associate professor of information technology and public policy at Carnegie Mellon's H. John Heinz III College and a researcher in the Carnegie Mellon CyLab.

More from IDG News Service on a study published in a journal Monday. The researchers' work will also be discussed at the BlackHat conferencing upcoming in Las Vegas this summer.

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The future of networking as seen through the works of university and other labs.

Our mission is to give you a peek into the future of networking by tracking "alpha" research at university and other labs and at companies based on this work. Your Alpha Doggs editor is Bob Brown, Network World Online Executive Editor, News.