Security of Edge AI Against Hardware Attacks

Security of Edge AI Against Hardware Attacks

tinyML via YouTube Direct link

Increasing Traces

12 of 38

12 of 38

Increasing Traces

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Security of Edge AI Against Hardware Attacks

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  1. 1 Introduction
  2. 2 Overview
  3. 3 Side channel analysis
  4. 4 Differential power analysis
  5. 5 Fault attacks
  6. 6 Neural Network
  7. 7 Network Structure
  8. 8 Neuron Parameters
  9. 9 Power Trace
  10. 10 Activation Function
  11. 11 Retrieving Weights
  12. 12 Increasing Traces
  13. 13 Results
  14. 14 Counter measures
  15. 15 Masking
  16. 16 Takeaways
  17. 17 Questions
  18. 18 Thank you
  19. 19 Poll
  20. 20 Q1 How many neurons do the mentioned MLCN networks contain
  21. 21 How many neurons do the mentioned MLCN networks contain
  22. 22 How well does it scale with the network size
  23. 23 Does it make any difference
  24. 24 Generating adversarial examples
  25. 25 IP theft
  26. 26 Least negative impact
  27. 27 Hardware counter measures
  28. 28 How successful is an attack
  29. 29 Prior Knowledge
  30. 30 Random Input
  31. 31 Retrieve Network
  32. 32 Network Security
  33. 33 Parallel Implementation
  34. 34 Noise
  35. 35 Other attacks
  36. 36 Summary
  37. 37 Audience questions
  38. 38 Sponsors

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