Risk
7/7/2009
05:48 PM
Connect Directly
Google+
LinkedIn
Twitter
RSS
E-Mail
50%
50%

Social Security Number Prediction Makes Identity Theft Easy

Posting your birthday on Facebook could help identity thieves predict your Social Security number, a new study finds.

Online information about your date of birth and place of birth could allow identity thieves to guess your Social Security number, according to a paper by two Carnegie Mellon researchers.

The paper, published on Monday in The Proceedings of the National Academy of Sciences, details the "unexpected privacy consequences" that arise when disparate data sources can be correlated.

The authors of the study, Alessandro Acquisti, an associate professor of information technology and public policy at CMU's Heinz College, and Ralph Gross, a postdoctoral researcher, demonstrate that Social Security numbers can be predicted using basic demographic data gleaned from government data sources, commercial databases, voter registration lists, or online social networks.

Knowing a person's Social Security number (SSN), name, and date of birth is typically enough to allow an identity thief to impersonate that person for the purpose of various kinds of fraud. Thus, being able to easily guess a person's SSN presents a significant security risk.

Acquisti and Gross estimate that 10 million American residents publish their birthdays in online profiles, or provide enough information for their birthdays to be inferred.

The accuracy with which SSNs can be predicted in 100 attempts varies, based on the availability of online data and on the subject's date and place of birth, from 0.08% to over 10% for some states.

Such odds may not seem particularly dangerous, but an attacker could use a computer program to guess and guess again, over and over. With 1,000 attempts, a SSN becomes as easy to crack as a 3-digit PIN. Among those born recently in small states, the researchers were able to predict SSNs with 60% accuracy after 1,000 attempts.

In their paper, Acquisti and Gross pose a hypothetical scenario in which an attacker rents a 10,000 machine botnet to apply for credit cards in the names of 18-year-old residents of West Virginia using public data. Based on various assumptions, such as the number of incorrect SSN submissions allowed before a credit card issuer blacklists a submitting IP address (3), they estimate that an identity thief could obtain credit card accounts at a rate of up to 47 per minute, or 4,000 before every machine in the botnet got blocked.

Based on an estimated street price that ranges from $1 to $40 per stolen identity, identity thieves in theory could make anywhere from $2,830 to $112,800 per hour.

As a temporary defensive strategy, the authors recommend that the Social Security Administration fully randomize the assignment of new SSNs, instead of randomizing only the first three digits, as the agency recently proposed. But, they note, such measures would not protect existing SSNs.

They also suggest that legislative defenses, such as SSN redaction requirements, won't work either.

"Industry and policy makers may need, instead, to finally reassess our perilous reliance on SSNs for authentication, and on consumers' impossible duty to protect them," the paper concludes.

Comment  | 
Print  | 
More Insights
Register for Dark Reading Newsletters
White Papers
Cartoon
Current Issue
Dark Reading Tech Digest, Dec. 19, 2014
Software-defined networking can be a net plus for security. The key: Work with the network team to implement gradually, test as you go, and take the opportunity to overhaul your security strategy.
Flash Poll
Video
Slideshows
Twitter Feed
Dark Reading - Bug Report
Bug Report
Enterprise Vulnerabilities
From DHS/US-CERT's National Vulnerability Database
CVE-2014-8802
Published: 2015-01-23
The Pie Register plugin before 2.0.14 for WordPress does not properly restrict access to certain functions in pie-register.php, which allows remote attackers to (1) add a user by uploading a crafted CSV file or (2) activate a user account via a verifyit action.

CVE-2014-9623
Published: 2015-01-23
OpenStack Glance 2014.2.x through 2014.2.1, 2014.1.3, and earlier allows remote authenticated users to bypass the storage quote and cause a denial of service (disk consumption) by deleting an image in the saving state.

CVE-2014-9638
Published: 2015-01-23
oggenc in vorbis-tools 1.4.0 allows remote attackers to cause a denial of service (divide-by-zero error and crash) via a WAV file with the number of channels set to zero.

CVE-2014-9639
Published: 2015-01-23
Integer overflow in oggenc in vorbis-tools 1.4.0 allows remote attackers to cause a denial of service (crash) via a crafted number of channels in a WAV file, which triggers an out-of-bounds memory access.

CVE-2014-9640
Published: 2015-01-23
oggenc/oggenc.c in vorbis-tools 1.4.0 allows remote attackers to cause a denial of service (out-of-bounds read) via a crafted raw file.

Best of the Web
Dark Reading Radio
Archived Dark Reading Radio
If you’re a security professional, you’ve probably been asked many questions about the December attack on Sony. On Jan. 21 at 1pm eastern, you can join a special, one-hour Dark Reading Radio discussion devoted to the Sony hack and the issues that may arise from it.