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Deriving Mother’s Maiden Names Using Public Records Virgil Griffith Undergraduate Research Assistant Indiana University DIMACS Security.

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Presentation on theme: "Deriving Mother’s Maiden Names Using Public Records Virgil Griffith Undergraduate Research Assistant Indiana University DIMACS Security."— Presentation transcript:

1 Deriving Mother’s Maiden Names Using Public Records Virgil Griffith Undergraduate Research Assistant Indiana University DIMACS Security Workshop Rutgers University

2 Our Approach  Data-mine online public records databases which are required by law to be public  Use heuristics to deduce maiden names  On a large enough scale, even the easiest cases lead to massive compromise.  Could be applied anywhere, for simplicity we focused only on Texas.

3 Why Texas?  Large population  Significant in of itself  Closer to national averages than California.  Large states have good online records.

4 Surveying Potentially Useful Public Records  US National Census  Voter Registration Records  Property Records  Phonebooks  Newspaper Obituaries  Social Security Death Index  Marriage Records  Birth Records 

5 Searching for Free Birth/Marriage Records Add 4,499 Texans Fully Compromised: 4,499  Mormons  Searchsystems.net County Records Found: 12 Marriage Indexes 7 Birth Indexes County Records Found: 12 Marriage Indexes 7 Birth Indexes  Rootsweb.com’s WorldConnect Family Tree’s for 4,499 Living Texans  Rootsweb’s USGenWeb  Texas Bureau of Vital Statistics 

6 Texas Dept. of Vital Stats  State archive for all vital information  Marriage index Online  Divorce index Online  +6,174,968 Marriage Records Informs us that…  In Oct Birth indexes taken offline  In June 2002 Death indexes also taken offline  +2,431,967 Birth Records Texans Fully Compromised: 4,499

7 Low Hanging Fruit in Birth Records  Births have MMN in plaintext!  1,114,680 Males Auto-compromised  1,069,448 Females in records  Connecting females born to Marriages gives 288,751 compromises (~27%).  has 40,697 hyphenated last names +1,114, ,751 Texans Fully Compromised: 1,407,930

8 Analysis: Work So Far 1.Children will have same last name as their parents 2.Suffixed Children will have same first and last name as parents 3.Children often born shortly after parents’ marriage 4.Children born shortly after parents’ marriage often born in same county. Attackers don’t have to pick the correct parents,just the correct MMN! Texans Fully Compromised: 1,407,930

9 Example #1 Ernest AAKQUANAHANN Dionne COX Mother’s Maiden Name = COX Entropy = 0 bits Texans Fully Compromised: 1,407,930

10 Example #2 Shawn ZUTTER Lisa MENDOZA Chad ZUTTER Lauren LANDGREBE Mother’s Maiden Name = ? Entropy = 1 bit Texans Fully Compromised: 1,407,930

11 Example #3 Robert STUGON Duarte STURNER Jim STUGON Luann STURNER Mother’s Maiden Name = STURNER Entropy = 0 bits Texans Fully Compromised: 1,407,930

12 Texans Compromised: 1,407,930 Results: Knowing Victim’s Lastname

13 Results: % Marriages Compromised via Last Name +82,272 Texans Fully Compromised: 1,490,202

14 Results: Suffixed Children +344,463 Texans Fully Compromised: 1,834,655

15 Results: Knowing Victim’s Lastname + Age Texans Fully Compromised: 1,834,655

16 Work In Progress: Assuming born 5 years from Marriage + Same County +2,355,828 Texans Fully Compromised: 4,190,493

17 Future Work  Add more birth records to see if % birth compromises goes up.  Parents’ names often repeated in their children’s names.  Factor in Groom’s suffix when looking for Suffix Children  Factor in Divorce Records  Factor in SSDI/State Death Records FINAL Texans Compromised: 4,190,493 ~20.09% of state population

18 End Work further described in: V. Griffith, M. Jakobsson (2005) Messin’ with Texas: Deriving Mother’s Maiden Names Using Public Records


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