Overview
Syllabus
Introduction
Overview
Side channel analysis
Differential power analysis
Fault attacks
Neural Network
Network Structure
Neuron Parameters
Power Trace
Activation Function
Retrieving Weights
Increasing Traces
Results
Counter measures
Masking
Takeaways
Questions
Thank you
Poll
Q1 How many neurons do the mentioned MLCN networks contain
How many neurons do the mentioned MLCN networks contain
How well does it scale with the network size
Does it make any difference
Generating adversarial examples
IP theft
Least negative impact
Hardware counter measures
How successful is an attack
Prior Knowledge
Random Input
Retrieve Network
Network Security
Parallel Implementation
Noise
Other attacks
Summary
Audience questions
Sponsors
Taught by
tinyML