Hardware security and trust have become a pressing issue during the last two decades due
to the globalization of the semiconductor supply chain and ubiquitous network connection of …

Currently, Machine Learning (ML) is becoming ubiquitous in everyday life. Deep Learning
(DL) is already present in many applications ranging from computer vision for medicine to …

As “deep neural networks”(DNNs) achieve increasing accuracy, they are getting employed
in increasingly diverse applications, including security-critical applications such as medical …

Deep learning is vulnerable to adversarial attacks, where carefully-crafted input
perturbations could mislead a well-trained Deep Neural Network (DNN) to produce incorrect …

The recent breakthroughs of deep neural networks (DNNs) and the advent of billions of
Internet of Things (IoT) devices have excited an explosive demand for intelligent IoT devices …

With the increasing proliferation of hardware accelerators and the predicted continued
increase in the heterogeneity of future computing systems, it is necessary to understand the …

Hardware accelerator-based CNNs (HA-CNNs), particularly those based on FPGAs, are
becoming increasingly popular for accelerating inference due to their ease of prototyping …

Deep learning (DL) models are enabling a significant paradigm shift in a diverse range of
fields, including natural language processing and computer vision, as well as the design …

Hyperdimensional Computing (HDC), also known as Vector Symbolic Architecture (VSA), is
an emerging AI algorithm inspired by the way the human brain functions. Compared with …

DNNs are known to be vulnerable to so-called adversarial attacks that manipulate inputs to
cause incorrect results that can be beneficial to an attacker or damaging to the victim …