Deep Learning is the most widely used tool in the contemporary field of computer vision. Its
ability to accurately solve complex problems is employed in vision research to learn deep …

This work provides the community with a timely comprehensive review of backdoor attacks
and countermeasures on deep learning. According to the attacker's capability and affected …

Deep learning is at the heart of the current rise of artificial intelligence. In the field of
computer vision, it has become the workhorse for applications ranging from self-driving cars …

Several years of research have shown that machine-learning systems are vulnerable to
adversarial examples, both in theory and in practice. Until now, such attacks have primarily …

Recent years have seen a proliferation of research on adversarial machine learning.
Numerous papers demonstrate powerful algorithmic attacks against a wide variety of …

After a plethora of high-profile RowHammer attacks, CPU and DRAM vendors scrambled to
deliver what was meant to be the definitive hardware solution against the RowHammer …

Abstract Security of modern Deep Neural Networks (DNNs) is under severe scrutiny as the
deployment of these models become widespread in many intelligence-based applications …

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 …

Memory isolation is critical for system reliability, security, and safety. Unfortunately, read
disturbance can break memory isolation in modern DRAM chips. For example, RowHammer …

The RowHammer vulnerability in DRAM is a critical threat to system security. To protect
against RowHammer, vendors commit to security-through-obscurity: modern DRAM chips …