University of Geneva

Defending against adversarial attacks by randomized diversification

The chain of the first 3 blocks can be organized in a parallel multi-channel structure that is followed by one or several aggregation blocks. The final decision about the class is made based on the ...
IEEE

Reinforcing Adversarial Transferability via Negative Class Guided Example Generation

Abstract: Recent studies have revealed that Deep Neural Networks (DNNs) are highly vulnerable to adversarial examples, which are generated by introducing imperceptible perturbations to clean images, ...
JD Supra

FCC Imposes Broad 'Foreign Adversary Control' Reporting Requirements

The FCC has enforced foreign ownership restrictions for certain spectrum licensees and other regulated entities for decades under its organic act, the Communications Act of 1934, as amended. However, ...
marktechpost

How to Design Complex Deep Learning Tensor Pipelines Using Einops with Vision, Attention, and Multimodal Examples

In this tutorial, we walk through advanced usage of Einops to express complex tensor transformations in a clear, readable, and mathematically precise way. We demonstrate how rearrange, reduce, repeat, ...
Breaking Defense

AI ‘fundamentally changing’ adversary behavior, leading to force generation reforms: Official

Sailors assigned to Navy Cyber Defense Operations Command monitor, analyze, detect and respond to unauthorized activity within U.S. Navy information systems and computer networks. NCDOC is responsible ...
IEEE

Boosting Adversarial Transferability of Vision Transformers

Abstract: Vision Transformers (ViTs) have emerged as a dominant backbone architecture for a variety of visual tasks; however, their vulnerability to adversarial examples continues to pose a ...