Concern over the privacy of those numbers has grown in the wake of hundreds of data breaches reported by businesses, governments and educational institutions, breaches that have exposed millions of consumer records -- including SSNs.
In recent years, a number of states have passed legislation to redact or remove the numbers from public documents, such as divorce and property records, and bankruptcy filings. In addition, legislation introduced this year by Rep. Rodney Frelinghuysen (R-N.J.) and Sen. Dianne Feinstein (D-Calif.) would prohibit the display, sale, or purchase of Social Security numbers without consent, and would bar businesses from requiring people to provide their number.
The researchers at Carnegie Mellon set out to see if they could discover people's numbers by first exploiting what is publicly known about how the numbers are derived.
The Social Security number's first three digits -- called the "area number" -- is issued according to the Zip code of the mailing address provided in the application form. The fourth and fifth digits -- known as the "group number" -- transition slowly, and often remain constant over several years for a given region. The last four digits are assigned sequentially.
As a result, SSNs assigned in the same state to applicants born on consecutive days are likely to contain the same first four or five digits, particularly in states with smaller populations and rates of birth.
As it happens, the researchers said, if you're trying to discover a living person's SSN, the best place to start is with a list of dead people -- particularly deceased people who were born around the time and place of your subject. The so-called "Death Master File," is a publicly available file which lists SSNs, names, dates of birth and death, and the states of all individuals who have applied for a number and whose deaths have been reported to the Social Security Administration.
CMU researchers Acquisti and Ph.D student Ralph Gross theorized that they could use the Death Master File along with publicly available birth information to predict narrow ranges of values wherein individual SSNs were likely to fall. The two tested their hunch using the Death
Master File of people who died between 1972 and 2003, and found that on the first try they could correctly guess the first five digits of the SSN for 44 percent of deceased people who were born after 1988, and for 7 percent of those born between 1973 and 1988.
Acquisti and Gross found that it was far easier to predict SSNs for people born after 1988, when the Social Security Administration began an effort to ensure that U.S. newborns obtained their SSNs shortly after birth.
They were able to identify all nine digits for 8.5 percent of people born after 1988 in fewer than 1,000 attempts. For people born recently in smaller states, researchers sometimes needed just 10 or fewer attempts to predict all nine digits.
Records of an individual's state and date of birth can be obtained from a variety of sources, including voter registration lists and commercial databases. What's more, many people now self-publish this information as part of their personal profiles on blogs and social networking sites. Indeed, the researchers tested their method using birthdays and hometowns that CMU students published on social networking sites, with similar results.
Privacy and security experts praised the Carnegie Mellon study, saying it should be a wake-up call to policy makers and industry leaders, many of whom have resisted switching to a more secure consumer authentication system due to the sheer cost of changing the current system.
"Sure, the study says that if you were born in a big state on a busy day you're probably still safe," from having identity thieves guess your entire SSN, Anderson said. "Still, I think many people would find it unacceptable that a system continues in use which in effect exposes tens of millions of Americans to fraud and other kinds of harm."
"Because of the way the SSN has been designed, asking for the last four numbers of the SSN puts people at risk because those are the only numbers that are unique to you and cannot be guessed easily by someone who might want to use your identity,"
In recent years, a number of states have passed legislation to redact or remove the numbers from public documents, such as divorce and property records, and bankruptcy filings. In addition, legislation introduced this year by Rep. Rodney Frelinghuysen (R-N.J.) and Sen. Dianne Feinstein (D-Calif.) would prohibit the display, sale, or purchase of Social Security numbers without consent, and would bar businesses from requiring people to provide their number.
The researchers at Carnegie Mellon set out to see if they could discover people's numbers by first exploiting what is publicly known about how the numbers are derived.
The Social Security number's first three digits -- called the "area number" -- is issued according to the Zip code of the mailing address provided in the application form. The fourth and fifth digits -- known as the "group number" -- transition slowly, and often remain constant over several years for a given region. The last four digits are assigned sequentially.
As a result, SSNs assigned in the same state to applicants born on consecutive days are likely to contain the same first four or five digits, particularly in states with smaller populations and rates of birth.
As it happens, the researchers said, if you're trying to discover a living person's SSN, the best place to start is with a list of dead people -- particularly deceased people who were born around the time and place of your subject. The so-called "Death Master File," is a publicly available file which lists SSNs, names, dates of birth and death, and the states of all individuals who have applied for a number and whose deaths have been reported to the Social Security Administration.
CMU researchers Acquisti and Ph.D student Ralph Gross theorized that they could use the Death Master File along with publicly available birth information to predict narrow ranges of values wherein individual SSNs were likely to fall. The two tested their hunch using the Death
Master File of people who died between 1972 and 2003, and found that on the first try they could correctly guess the first five digits of the SSN for 44 percent of deceased people who were born after 1988, and for 7 percent of those born between 1973 and 1988.
Acquisti and Gross found that it was far easier to predict SSNs for people born after 1988, when the Social Security Administration began an effort to ensure that U.S. newborns obtained their SSNs shortly after birth.
They were able to identify all nine digits for 8.5 percent of people born after 1988 in fewer than 1,000 attempts. For people born recently in smaller states, researchers sometimes needed just 10 or fewer attempts to predict all nine digits.
Records of an individual's state and date of birth can be obtained from a variety of sources, including voter registration lists and commercial databases. What's more, many people now self-publish this information as part of their personal profiles on blogs and social networking sites. Indeed, the researchers tested their method using birthdays and hometowns that CMU students published on social networking sites, with similar results.
Privacy and security experts praised the Carnegie Mellon study, saying it should be a wake-up call to policy makers and industry leaders, many of whom have resisted switching to a more secure consumer authentication system due to the sheer cost of changing the current system.
"Sure, the study says that if you were born in a big state on a busy day you're probably still safe," from having identity thieves guess your entire SSN, Anderson said. "Still, I think many people would find it unacceptable that a system continues in use which in effect exposes tens of millions of Americans to fraud and other kinds of harm."
"Because of the way the SSN has been designed, asking for the last four numbers of the SSN puts people at risk because those are the only numbers that are unique to you and cannot be guessed easily by someone who might want to use your identity,"
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