- By analyzing a public data set called the “Death Master File,” which contains SSNs and birth information for people who have died, computer scientists from Carnegie Mellon University discovered distinct patterns in how the numbers are assigned. In many cases, knowing the date and state of an individual’s birth was enough to predict a person’s SSN.
- “We didn’t break any secret code or hack into an undisclosed data set,” said privacy expert Alessandro Acquisti, co-author of the study published Monday in the journal Proceedings of the National Academy of Sciences. “We used only publicly available information, and that’s why our result is of value. It shows that you can take personal information that’s not sensitive, like birth date, and combine it with other publicly available data to come up with something very sensitive and confidential.”
- With just two attempts, the researchers correctly guessed the first five digits of SSNs for 60 percent of deceased Americans born between 1989 and 2003. With fewer than 1,000 attempts, they could identify the entire nine digits for 8.5 percent of the group.
- There’s only a few short steps between making a statistical prediction about a person’s SSN and verifying their actual number, Acquisti said. Through a process called “tumbling,” hackers can exploit instant online credit approval services — or even the Social Security Administration’s own verification database — to test multiple numbers until they find the right one. Although these services usually block users after several failed attempts, criminals can use networks of compromised computers called botnets to scan thousands of numbers at a time.
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thakker reblogged this from roads2roam and added:
This is important. Also, this is one example (among many) of why it is important for mathematical understanding to be...
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roads2roam reblogged this from ledgergermane
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ledgergermane posted this
