Faces of Facebook - Or, How the Largest Real ID Database in the World Came to Be

Faces of Facebook - Or, How the Largest Real ID Database in the World Came to Be

Black Hat via YouTube Direct link

Experiment 2: Results

24 of 43

24 of 43

Experiment 2: Results

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Faces of Facebook - Or, How the Largest Real ID Database in the World Came to Be

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  1. 1 Intro
  2. 2 A tale of two futures
  3. 3 Back to the past
  4. 4 Background
  5. 5 of various technologies (2/2)
  6. 6 What is different: The convergence
  7. 7 Our research focus
  8. 8 A short facial taxonomy
  9. 9 In a nutshell
  10. 10 Why this matters
  11. 11 What this implies
  12. 12 Key themes
  13. 13 Experiments
  14. 14 Source DB
  15. 15 Experimenti
  16. 16 Experiment 1: Approach
  17. 17 Experiment 1: Ground truth
  18. 18 Experiment 1: Evaluation
  19. 19 Experiment 1: Results
  20. 20 Experiment 1: Comments
  21. 21 Experiment 2: Process
  22. 22 Experiment 2: Approach
  23. 23 Experiment 2: Examples
  24. 24 Experiment 2: Results
  25. 25 Pushing the envelope
  26. 26 Chances of correctly matching SSN digits by random guess, under status quo knowledge
  27. 27 SSN assignment patterns: Two representative States
  28. 28 Chances of correctly matching SSN digits by random guess, under our algorithm
  29. 29 Predicting SSNs from public data
  30. 30 Can you do 1+1? Experiment 3
  31. 31 A picture is worth a thousand words
  32. 32 Data "accretion"
  33. 33 Not a trivial problem
  34. 34 Privacy in the Age of Augmented Reality
  35. 35 Screenshots
  36. 36 What is in real time, and what is not
  37. 37 Limitations
  38. 38 Extrapolations
  39. 39 Scalability: Availability of images (2/2)
  40. 40 Scalability: Cooperative subjects
  41. 41 Scalability: Geographical restrictions
  42. 42 Implications (2/4)
  43. 43 No clear solution

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