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The Social Security Number Crisis

The Social Security Number Crisis

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The Social Security Number Crisis

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  1. The Social Security Number Crisis Latanya Sweeney privacy.cs.cmu.edu

  2. Questions Addressed in this Lecture How are Social Security numbers assigned? What predictions can we make about a person and his SSN? If we have a person’s Social Security number, can we get a credit card in her name? Show me someone who gives his Social Security number away for free. Give me a solution to consider.

  3. Thanks to Harry Lewis Henry Leitner Harvard Center for Research on Computation and Society

  4. Gratitude to Harvard Extension School Harvard Summer School Harvard GSAS Harvard College for exposing me to other disciplines and other ways of thinking.

  5. Privacy Technology • Example: linking data • Example: anonymizing data • Example: distributed surveillance • Example: trails of dots • Example: learning who you know • Example: identity theft • Example: fingerprint capture • Example: bio-terrorism surveillance • Example: privacy-preserving surveillance • Example: DNA privacy • Example: SSN failures and biometrics • Example: k-Anonymity • Example: webcam surveillance • Example: text de-identification • Example: face de-identification • Example: fraudulent Spam privacy.cs.cmu.edu

  6. Data Detective How do we learn sensitive or strategic information from seemingly innocent information? Data Protector How do we provably prevent sensitive or strategic information from being learned?

  7. Privacy Technology • Example: linking data • Example: anonymizing data • Example: distributed surveillance • Example: trails of dots • Example: learning who you know • Example: identity theft • Example: fingerprint capture • Example: bio-terrorism surveillance • Example: privacy-preserving surveillance • Example: DNA privacy • Example: SSN failures and biometrics • Example: k-Anonymity • Example: webcam surveillance • Example: text de-identification • Example: face de-identification • Example: fraudulent Spam privacy.cs.cmu.edu

  8. Privacy Technology • Example: linking data • Example: anonymizing data • Example: distributed surveillance • Example: trails of dots • Example: learning who you know • Example: identity theft • Example: fingerprint capture • Example: bio-terrorism surveillance • Example: privacy-preserving surveillance • Example: DNA privacy • Example: SSN failures and biometrics • Example: k-Anonymity • Example: webcam surveillance • Example: text de-identification • Example: face de-identification • Example: fraudulent Spam privacy.cs.cmu.edu

  9. Privacy Technology • Example: linking data • Example: anonymizing data • Example: distributed surveillance • Example: trails of dots • Example: learning who you know • Example: identity theft • Example: fingerprint capture • Example: bio-terrorism surveillance • Example: privacy-preserving surveillance • Example: DNA privacy • Example: SSN failures and biometrics • Example: k-Anonymity • Example: webcam surveillance • Example: text de-identification • Example: face de-identification • Example: fraudulent Spam privacy.cs.cmu.edu

  10. Privacy Technology • Example: linking data • Example: anonymizing data • Example: distributed surveillance • Example: trails of dots • Example: learning who you know • Example: identity theft • Example: fingerprint capture • Example: bio-terrorism surveillance • Example: privacy-preserving surveillance • Example: DNA privacy • Example: SSN failures and biometrics • Example: k-Anonymity • Example: webcam surveillance • Example: text de-identification • Example: face de-identification • Example: fraudulent Spam privacy.cs.cmu.edu

  11. Privacy Technology • Example: linking data • Example: anonymizing data • Example: distributed surveillance • Example: trails of dots • Example: learning who you know • Example: identity theft • Example: fingerprint capture • Example: bio-terrorism surveillance • Example: privacy-preserving surveillance • Example: DNA privacy • Example: SSN failures and biometrics • Example: k-Anonymity • Example: webcam surveillance • Example: text de-identification • Example: face de-identification • Example: fraudulent Spam privacy.cs.cmu.edu

  12. Privacy Technology • Example: linking data • Example: anonymizing data • Example: distributed surveillance • Example: trails of dots • Example: learning who you know • Example: identity theft • Example: fingerprint capture • Example: bio-terrorism surveillance • Example: privacy-preserving surveillance • Example: DNA privacy • Example: Identity theft protections • Example: k-Anonymity • Example: webcam surveillance • Example: text de-identification • Example: face de-identification • Example: fraudulent Spam privacy.cs.cmu.edu

  13. Privacy Technology • Example: linking data • Example: anonymizing data • Example: distributed surveillance • Example: trails of dots • Example: learning who you know • Example: identity theft • Example: fingerprint capture • Example: bio-terrorism surveillance • Example: privacy-preserving surveillance • Example: DNA privacy • Example: Identity theft protections • Example: k-Anonymity • Example: webcam surveillance • Example: text de-identification • Example: face de-identification • Example: fraudulent Spam Original Tracked De-Identified privacy.cs.cmu.edu

  14. Privacy Technology • Example: linking data • Example: anonymizing data • Example: distributed surveillance • Example: trails of dots • Example: learning who you know • Example: identity theft • Example: fingerprint capture • Example: bio-terrorism surveillance • Example: privacy-preserving surveillance • Example: DNA privacy • Example: SSN failures and biometrics • Example: k-Anonymity • Example: webcam surveillance • Example: text de-identification • Example: face de-identification • Example: fraudulent Spam privacy.cs.cmu.edu

  15. Privacy Technology • Example: linking data • Example: anonymizing data • Example: distributed surveillance • Example: trails of dots • Example: learning who you know • Example: identity theft • Example: fingerprint capture • Example: bio-terrorism surveillance • Example: privacy-preserving surveillance • Example: DNA privacy • Example: SSN failures and biometrics • Example: k-Anonymity • Example: webcam surveillance • Example: text de-identification • Example: face de-identification • Example: fraudulent Spam privacy.cs.cmu.edu

  16. Privacy Technology • Example: linking data • Example: anonymizing data • Example: distributed surveillance • Example: trails of dots • Example: learning who you know • Example: identity theft • Example: fingerprint capture • Example: bio-terrorism surveillance • Example: privacy-preserving surveillance • Example: DNA privacy • Example: SSN failures and biometrics • Example: k-Anonymity • Example: webcam surveillance • Example: text de-identification • Example: face de-identification • Example: fraudulent Spam privacy.cs.cmu.edu

  17. Privacy Technology • Example: tracking people • Example: anonymizing data • Example: distributed surveillance • Example: trails of dots • Example: learning who you know • Example: identity theft • Example: fingerprint capture • Example: bio-terrorism surveillance • Example: privacy-preserving surveillance • Example: DNA privacy • Example: Identity theft protections • Example: k-Anonymity • Example: webcam surveillance • Example: text de-identification • Example: face de-identification • Example: fraudulent Spam privacy.cs.cmu.edu

  18. Privacy Technology • Example: linking data • Example: anonymizing data • Example: distributed surveillance • Example: trails of dots • Example: learning who you know • Example: identity theft • Example: fingerprint capture • Example: bio-terrorism surveillance • Example: privacy-preserving surveillance • Example: DNA privacy • Example: SSN failures and biometrics • Example: k-Anonymity • Example: webcam surveillance • Example: text de-identification • Example: face de-identification • Example: fraudulent Spam privacy.cs.cmu.edu

  19. Privacy Technology • Example: linking data • Example: anonymizing data • Example: distributed surveillance • Example: trails of dots • Example: learning who you know • Example: identity theft • Example: fingerprint capture • Example: bio-terrorism surveillance • Example: privacy-preserving surveillance • Example: DNA privacy • Example: SSN failures and biometrics • Example: k-Anonymity • Example: webcam surveillance • Example: text de-identification • Example: face de-identification • Example: fraudulent Spam privacy.cs.cmu.edu

  20. Team Members • Computer scientists (AI, database, security, theory, NLP, HCI, data mining, vision, biometrics, link analysis) • Lawyers • Social scientists • Geneticists • Ethicists • Medical doctors • Policy analysts • Forensic scientists • Economists

  21. Questions Addressed in this Lecture How are Social Security numbers assigned? What predictions can we make about a person and his SSN? If we have a person’s Social Security number, can we get a credit card in her name? Show me someone who gives his Social Security number away for free. Give me a solution to consider.

  22. SSN Numbering Scheme • Social Security number allocations • Historical highlights and uses • Inferences from SSNs

  23. Historical Highlights of the SSN • 1935 Social Security Act SSNs only to be used for the social security program. • 1943 Executive Order 9397 Required federal agencies to use SSNs in new record systems • 1961 IRS began using SSN As taxpayer identification number • 1974 Privacy Act Government agencies use of SSN required authorization and disclosures (exempt agencies already using SSN) • 1976 Tax Reform Act Granted authority to State and local governments to use SSNs: state and local taxes, motor vehicle agencies • Over 400 million different numbers have been issued. Source: Social Security Administration, http://www.ssa.gov/history/hfaq.html

  24. Non-Government Uses of SSN • Corporate use of the SSN is not bound by the laws and regulations mentioned earlier. • You can request an alternative number from companies. You can refuse to provide, they can refuse service. • Most common non-government use relates to credit bureaus and credit granting companies who rely on the number for: • Recognition – to locate your credit history for sharing it with you or with others from whom you requested credit. • Authentication – to make sure new entries are added to the credit report that relates to you. Primary means is SSN along with mother’s maiden name, which serves as a kind of password. • Common uses are as corporate identification numbers: Example: medical and school identification cards

  25. Quality of the SSN Assignment Ability to acquire the number and use it falsely grows as more copies of the number are stored for different purposes while possible benefits of misuse have rewards (even if illegal). A Social Security number is almost always specific to one person and one person typically has a unique SSN. There are exceptions.

  26. Unusual case of SSN 078-05-1120 Used by thousands of People! In 1938, a wallet manufacturer provided a sample SSN card, inserted in each new wallet. The company’s Vice President used the actual SSN of his secretary, Mrs. Hilda Schrader Whitcher. The wallet was sold by Woolworth and other stores. Even though it had the word "specimen" written across the face, many purchasers of the wallet adopted the SSN as their own. In the peak year of 1943, 5,755 people were using it. SSA voided the number. (Mrs. Whitcher was given a new number.) In total, over 40,000 people reported this as their SSN. As late as 1977, 12 people were still using it. Source: Social Security Administration, http://www.ssa.gov/history/ssn/misused.html

  27. SSN Numbering Scheme • Social Security number allocations • Historical highlights and uses • Inferences from SSNs

  28. SSNs are Encoded Numbers The encoding is based on how the numbers are issued. They typically situate the recipient in a geographical area within a time range. They may also reveal whether the person is an immigrant, an alien, or a worker on the railroad. Format: AAA-GG-NNNN AAA is area code GG is group code NNNN is serially assigned number

  29. First 3 digits Provide the State of Issuance, 1 001-003 New Hampshire 004-007 Maine 008-009 Vermont 010-034 Massachusetts 035-039 Rhode Island 040-049 Connecticut 050-134 New York 135-158 New Jersey 159-211 Pennsylvania 212-220 Maryland 221-222 Delaware 223-231 Virginia 691-699* 232-236 West Virginia 232 North Carolina 237-246 681-690 247-251 South Carolina 654-658 252-260 Georgia 667-675 261-267 Florida 589-595 766-772 268-302 Ohio 303-317 Indiana Source: Social Security Administration, http://www.ssa.gov/foia/stateweb.html

  30. First 3 digits Provide the State of Issuance, 2 318-361 Illinois 362-386 Michigan 387-399 Wisconsin 400-407 Kentucky 408-415 Tennessee 756-763* 416-424 Alabama 425-428 Mississippi 587-588 752-755* 429-432 Arkansas 676-679 433-439 Louisiana 659-665 440-448 Oklahoma 449-467 Texas 627-645 468-477 Minnesota 478-485 Iowa 486-500 Missouri 501-502 North Dakota 503-504 South Dakota 505-508 Nebraska 509-515 Kansas Source: Social Security Administration, http://www.ssa.gov/foia/stateweb.html

  31. First 3 digits Provide the State of Issuance, 3 516-517 Montana 518-519 Idaho 520 Wyoming 521-524 Colorado 650-653 525,585 New Mexico 648-649 526-527 Arizona 600-601 764-765 528-529 Utah 646-647 530 Nevada 680 531-539 Washington 540-544 Oregon 545-573 California 602-626 574 Alaska 575-576 Hawaii 750-751* 577-579 District of Columbia 580 Virgin Islands Source: Social Security Administration, http://www.ssa.gov/foia/stateweb.html

  32. First 3 digits Provide the State of Issuance, 4 580-584 Puerto Rico 596-599 586 Guam 586 American Samoa 586 Philippine Islands 700-728 Railroad Board** * Some states may share the same area by transfer or split. ** Railroad employees, discontinued July 1, 1963. 000 will NEVER start a valid SSN. Source: Social Security Administration, http://www.ssa.gov/foia/stateweb.html

  33. SSNs are Encoded Numbers The encoding is based on how the numbers are issued. They typically situate the recipient in a geographical area within a time range. They may also reveal whether the person is an immigrant, an alien, or a worker on the railroad. Format: AAA-GG-NNNN AAA is area code GG is group code NNNN is serially assigned number

  34. Digits 4 and 5, Order of Issuance • Called the Group numbers. Not assigned sequentially, but in the following order: • ODD - 01, 03, 05, 07, 09  • EVEN - 10 to 98 • After all in 98 are assigned, then • EVEN - 02, 04, 06, 08  • ODD - 11 to 99 Source: Social Security Administration, http://www.ssa.gov/foia/ssnweb.html

  35. High Group Listing On a regular basis, the Social Security Administration (SSA) publishes the highest group number that has been assigned for each area. Below is a sample of the first few entries for 9/2/2003. Source: Social Security Administration, http://www.ssa.gov/foia/highgroup.htm

  36. High Group Listing, How to Read On a regular basis, the Social Security Administration (SSA) publishes the highest group number that has been assigned for each area. Below is a sample of the first few entries for 9/2/2003. For area 003 (the first 3 digits of an SSN), the highest number used in the 4th and 5th digits is 96.

  37. High Group Listing, Interpretation • Recall the assignment of group numbers: • ODD - 01, 03, 05, 07, 09  then EVEN - 10 to 98 • After all in 98 are assigned, then • EVEN - 02, 04, 06, 08 then ODD - 11 to 99 003-09-1234 would be valid SSN.003-02-1234 would NOT be valid.

  38. What Can be Learned from the First 5 Digits of an SSN • In “semantic learning” terms, • The first 3 digits provide reliable inferences about place of issuance. • Digits 4 and 5 provide inferences on time of issuance.

  39. Questions Addressed in this Lecture How are Social Security numbers assigned? What predictions can we make about a person and his SSN? If we have a person’s Social Security number, can we get a credit card in her name? Show me someone who gives his Social Security number away for free. Give me a solution to consider.

  40. Social Security Death Index • The Social Security Administration releases the Social Security Death Index for public use. Perceived benefits: • genealogical research (constructing family trees) • attempt to defeat illegal re-use of SSNs. Released information for each death: NameSSNdate of birthdate of deathplace where SSN was issuedplace where SSN benefit was paid upon death

  41. Social Security Death Index Search by name or SSN, in art or whole. Advanced search includes options for date of birth, date of death, and geographical location, in part or whole. http://ssdi.genealogy.rootsweb.com/

  42. Sample Result for Herb Simon Search on Herbert Simon, Last residence was Pennsylvania.

  43. SSNwatch On-line SSN validation system. Given the first 3 or 5 digits of an SSN, returns the state in which the SSN was issued along with an estimated age range of the person. Sample uses: Job Applications Apartment Rentals Insurance Claims Student Applications http://privacy.cs.cmu.edu/dataprivacy/projects/ssnwatch/index.html

  44. SSNwatch Results for SSN 078-05- If the person presenting the SSN is about age 20, then it is extremely unlikely that the provided SSN was issued to that person.

  45. SSNwatch Results for SSN 078-05- If the person presenting the SSN fails to list or acknowledge New York as a prior residence, then it is extremely unlikely that the provided SSN was issued to that person.

  46. Lab Activity: Predicting an SSN from Facebook Profiles Take a moment and write down the steps (“algorithm”) needed to predict a SSN. Assume SSN is issued at birth. Your algorithm should predict the first 6 to 9 digits for Alice, who is born today in Cambridge, MA. (You don’t have to give me the answer, but tell me how to figure it out.)

  47. Lab Activity: Predicting an SSN from Facebook Profiles Recent finding: We can accurately predict 6 to 9 digits of a young person’s SSN.

  48. Questions Addressed in this Lecture How are Social Security numbers assigned? What predictions can we make about a person and his SSN? If we have a person’s Social Security number, can we get a credit card in her name? Show me someone who gives his Social Security number away for free. Give me a solution to consider.

  49. Federal Trade Commission Report: Victim Complaint Data The next group of slides are excerpts from the Federal Trade Commission Report on Identity Theft, Victim Complaint Data. Figures and Trends January-December 2001.

  50. Federal Trade Commission Report: Victim Complaint Data