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Differential privacy in the real world

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Yevgeniy Vahlis, Head of Applied Machine Learning, Borealis AI

Published in: Technology
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Differential privacy in the real world

  1. 1. our mandate:
  2. 2. who we are
  3. 3. Privacy Preserving AI
  4. 4. ● ● ● ● ● why privacy?
  5. 5. ● ● ● ● problem statement
  6. 6. But I’m removing PII??! ● ● ● ● 天涯人肉搜索引擎 ● Most organizations have processes for anonymizing and sanitizing data to protect privacy, however...
  7. 7. Toward real privacy & data aggregation ● ● ● ● You can create lasting differentiation by mathematically proving that your customers’ data is protected
  8. 8. Who is doing it? The 1st rule of DP club is that you don’t talk about DP club… unless you’re Apple
  9. 9. General property of security psychology
  10. 10. What is differential privacy?
  11. 11. Differential privacy ML Model ML Model ML Model Aggregate Model Data Data Data Add Noise “Differential privacy lets you gain insights from large datasets, but with a mathematical proof that no one can learn about a single individual.”
  12. 12. Differential privacy (non) guarantees ● ● ● ● ● ● ●
  13. 13. Differential privacy guarantees ● ○ ○ ○ ● 𝛆 ●
  14. 14. Differential privacy misconceptions ● ● ● ●
  15. 15. Technical crash course
  16. 16. Definition ● ● ●
  17. 17. Randomized response
  18. 18. Laplacian mechanism [Dwork06]
  19. 19. Teacher student model [PAEGT2017]
  20. 20. Examples of Use Cases ● ● ● ● ●

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