As the machine learning-related technology has made great progress in recent years, deep
neural networks are widely used in many scenarios, including security-critical ones, which …

Machine learning and in particular deep learning is used in a broad range of crucial
applications. Implementing such models in custom hardware can be highly beneficial thanks …

Prior attacks on graph neural networks have focused on graph poisoning and evasion,
neglecting the network's weights and biases. For convolutional neural networks, however …

DNNs have become pervasive in many security–critical scenarios such as autonomous
vehicles and medical diagnoses. Recent studies reveal the susceptibility of DNNs to various …

Bit Flip Attacks (BFAs) are a well-established class of adversarial attacks, originally
developed for Convolutional Neural Networks within the computer vision domain. Most …

Neural networks are widely used in critical environments such as healthcare, autonomous
vehicles, or video surveillance. To ensure the safety of the systems that rely on their …

In recent years, the Extreme Learning Machine (ELM) architecture has been widely applied
in various fields, leading to an increase in hardware attack attempts. However, the security …