Given the severe vulnerability of Deep Neural Networks (DNNs) against adversarial
examples, there is an urgent need for an effective adversarial attack to identify the …

Powered by advanced Artificial Intelligence (AI) techniques, conversational AI systems, such
as ChatGPT, and digital assistants like Siri, have been widely deployed in daily life …

Adversarial examples mislead deep neural networks with imperceptible perturbations and
have brought significant threats to deep learning. An important aspect is their transferability …

Transfer-based attack adopts the adversarial examples generated on the surrogate model to
attack various models, making it applicable in the physical world and attracting increasing …

Transfer-based attacks generate adversarial examples on the surrogate model, which can
mislead other black-box models without access, making it promising to attack real-world …

Deep neural networks are vulnerable to adversarial examples crafted by applying human-
imperceptible perturbations on clean inputs. Although many attack methods can achieve …

The exponential growth of social media platforms has brought about a revolution in
communication and content dissemination in human society. Nevertheless, these platforms …

Latent diffusion models achieve state-of-the-art performance on a variety of generative tasks,
such as image synthesis and image editing. However, the robustness of latent diffusion …

Abstract Language models are known to be vulnerable to textual adversarial attacks, which
add humanimperceptible perturbations to the input to mislead DNNs. It is thus imperative to …

The exponential growth of social media platforms, such as Facebook, Instagram, Youtube,
and TikTok, has revolutionized communication and content publication in human society …