Understanding Security Threats Against Machine - Deep Learning Applications

Understanding Security Threats Against Machine - Deep Learning Applications

Devoxx via YouTube Direct link

Introduction

1 of 18

1 of 18

Introduction

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Understanding Security Threats Against Machine - Deep Learning Applications

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  1. 1 Introduction
  2. 2 Review of Machine Learning
  3. 3 Example
  4. 4 Adversary Inputs
  5. 5 Neural Network
  6. 6 Why is this important
  7. 7 How does this work
  8. 8 Neural Networks
  9. 9 Whitebox vs Blackbox
  10. 10 Differentials
  11. 11 Derivative
  12. 12 math
  13. 13 fast gradient sign
  14. 14 Jacobian map approp approach
  15. 15 Carlini Wagner
  16. 16 Genetic Algorithms
  17. 17 Synthesising Data
  18. 18 Adversary Patches

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