4 papers
A Constant-Time Implementation Methodology for Activation Functions on Microcontrollers
Andrii Tyvodar, Andreas Rechberger, Dirmanto Jap +4
Embedded neural-network inference can leak information through timing side channels, including leakage caused by the evaluation of activation functions. This work proposes a consta…
Characterizing the Fault Response of the Intel Neural Compute Stick 2 Under Single-Pulse Electromagnetic Fault Injection
Å tefan KuÄerák, Jakub Breier, Xiaolu Hou
Vision processing units and other commercial neural-network inference accelerators are increasingly deployed in safety-relevant edge applications, but their fault response under tr…
Beyond TVLA: Anderson-Darling Leakage Assessment for Neural Network Side-Channel Leakage Detection
Ján Mikulec, Jakub Breier, Xiaolu Hou
Test Vector Leakage Assessment (TVLA) based on Welch's -test has become a standard tool for detecting side-channel leakage. However, its mean-based nature can limit sensitivity…
Make Shuffling Great Again: A Side-Channel Resistant Fisher-Yates Algorithm for Protecting Neural Networks
Leonard PuÅ¡káÄ, Marek BenoviÄ, Jakub Breier +1
Neural network models implemented in embedded devices have been shown to be susceptible to side-channel attacks (SCAs), allowing recovery of proprietary model parameters, such as w…