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Reverse engineering of deceptions on machine-and human-centric attacks
This work presents a comprehensive exploration of Reverse Engineering of Deceptions
(RED) in the field of adversarial machine learning. It delves into the intricacies of machine …
(RED) in the field of adversarial machine learning. It delves into the intricacies of machine …
Reverse engineering of imperceptible adversarial image perturbations
It has been well recognized that neural network based image classifiers are easily fooled by
images with tiny perturbations crafted by an adversary. There has been a vast volume of …
images with tiny perturbations crafted by an adversary. There has been a vast volume of …
Instant Adversarial Purification with Adversarial Consistency Distillation
Neural networks, despite their remarkable performance in widespread applications,
including image classification, are also known to be vulnerable to subtle adversarial noise …
including image classification, are also known to be vulnerable to subtle adversarial noise …
Adversarial attacks and robust defenses in deep learning
CP Lau, J Liu, WA Lin, H Souri, P Khorramshahi… - Handbook of …, 2023 - Elsevier
Deep learning models have shown exceptional performance in many applications, including
computer vision, natural language processing, and speech processing. However, if no …
computer vision, natural language processing, and speech processing. However, if no …
On trace of pgd-like adversarial attacks
Adversarial attacks pose security concerns to deep learning applications, but their
characteristics are under-explored. Yet largely imperceptible, a strong trace could have …
characteristics are under-explored. Yet largely imperceptible, a strong trace could have …
MMAD-Purify: A Precision-Optimized Framework for Efficient and Scalable Multi-Modal Attacks
Neural networks have achieved remarkable performance across a wide range of tasks, yet
they remain susceptible to adversarial perturbations, which pose significant risks in safety …
they remain susceptible to adversarial perturbations, which pose significant risks in safety …
Can Adversarial Examples Be Parsed to Reveal Victim Model Information?
Numerous adversarial attack methods have been developed to generate imperceptible
image perturbations that can cause erroneous predictions of state-of-the-art machine …
image perturbations that can cause erroneous predictions of state-of-the-art machine …