6 papers
Vogls: a Fast Interactive Full-timing Simulator for Pre-silicon Power Side-Channel Analysis
Gijs Burghoorn, Ileana Buhan, Lejla Batina
Designing hardware circuits resistant to side-channel attacks increasingly relies on simulation to predict device leakage before fabrication. Current functional verification simula…
Triggering Stealthy Feature Map Backdoors via Physical Fault Injection in Embedded Neural Networks
Steyn Hommes, Vincent Dankbaar, Tanguy Stekke +6
Fault injection (FI) attacks on embedded neural network (NN) implementations primarily focus on inducing misclassification by corrupting weights or intermediate computations, overl…
Kraken: Higher-order EM Side-Channel Attacks on DNNs in Near and Far Field
Peter Horvath, Ilia Shumailov, Lukasz Chmielewski +2
The multi-million dollar investment required for modern machine learning (ML) has made large ML models a prime target for theft. In response, the field of model stealing has emerge…
Emerging Threats and Countermeasures in Neuromorphic Systems: A Survey
Pablo Sorrentino, Stjepan Picek, Ihsen Alouani +5
Neuromorphic computing mimics brain-inspired mechanisms through spiking neurons and energy-efficient processing, offering a pathway to efficient in-memory computing (IMC). However,…
Real-world Edge Neural Network Implementations Leak Private Interactions Through Physical Side Channel
Zhuoran Liu, Senna van Hoek, Péter Horváth +3
Neural networks have become a fundamental component of numerous practical applications, and their implementations, which are often accelerated by hardware, are integrated into all…
BarraCUDA: Edge GPUs do Leak DNN Weights
Peter Horvath, Lukasz Chmielewski, Leo Weissbart +2
Over the last decade, applications of neural networks (NNs) have spread to various aspects of our lives. A large number of companies base their businesses on building products that…