research
∙
03/25/2023
A Desynchronization-Based Countermeasure Against Side-Channel Analysis of Neural Networks
Model extraction attacks have been widely applied, which can normally be...
share
research
∙
09/23/2021
FooBaR: Fault Fooling Backdoor Attack on Neural Network Training
Neural network implementations are known to be vulnerable to physical at...
research
∙
12/09/2020
Risk Management Framework for Machine Learning Security
Adversarial attacks for machine learning models have become a highly stu...
research
∙
02/23/2020
SNIFF: Reverse Engineering of Neural Networks with Fault Attacks
Neural networks have been shown to be vulnerable against fault injection...
research
∙
02/05/2019
Enhancing Fault Tolerance of Neural Networks for Security-Critical Applications
Neural Networks (NN) have recently emerged as backbone of several sensit...
research
∙
06/15/2018