Results 41 to 50 of about 543,217 (204)
Adversarial Attack Attribution: Discovering Attributable Signals in Adversarial ML Attacks
CoRR, 2021 Accepted to RSEML Workshop at AAAI ...
Marissa Dotter +5 more
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The model of network adversarial attack.
, 2022 (a) The structure of DCNN for experiment. (b) The model of network adversarial attack.
Zeyu Yu (9472333) +3 more
core +1 more source
Functional Adversarial Attacks
CoRR, 2019 Accepted to NeurIPS ...
Cassidy Laidlaw, Soheil Feizi
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Adversarial attacks and adversarial robustness in computational pathology
Nature Communications, 2022 Abstract Artificial Intelligence (AI) can support diagnostic workflows in oncology by aiding diagnosis and providing biomarkers directly from routine pathology slides. However, AI applications are vulnerable to adversarial attacks. Hence, it is essential to quantify and mitigate this risk before widespread clinical use.
Narmin Ghaffari Laleh +10 more
openaire +4 more sources
Augmented Lagrangian Adversarial Attacks [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 ICCV 2021 (Poster).
Jérôme Rony +3 more
openaire +3 more sources
Adversarial Attacks and Defenses
ACM SIGKDD Explorations Newsletter, 2021 Despite the recent advances in a wide spectrum of applications, machine learning models, especially deep neural networks, have been shown to be vulnerable to adversarial attacks. Attackers add carefully-crafted perturbations to input, where the perturbations are almost imperceptible to humans, but can cause models to make wrong predictions.
Ninghao Liu 0001 +4 more
openaire +3 more sources
Meta Gradient Adversarial Attack [PDF]
2021 IEEE/CVF International Conference on Computer Vision (ICCV), 2021 In recent years, research on adversarial attacks has become a hot spot. Although current literature on the transfer-based adversarial attack has achieved promising results for improving the transferability to unseen black-box models, it still leaves a long way to go. Inspired by the idea of meta-learning, this paper proposes a novel architecture called
Zheng Yuan 0005 +5 more
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Query complexity of adversarial attacks
CoRR, 2020 There are two main attack models considered in the adversarial robustness literature: black-box and white-box. We consider these threat models as two ends of a fine-grained spectrum, indexed by the number of queries the adversary can ask. Using this point of view we investigate how many queries the adversary needs to make to design an attack that is ...
Grzegorz Gluch, Rüdiger L. Urbanke
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Real-Time Adversarial Attacks [PDF]
Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019 In recent years, many efforts have demonstrated that modern machine learning algorithms are vulnerable to adversarial attacks, where small, but carefully crafted, perturbations on the input can make them fail. While these attack methods are very effective, they only focus on scenarios where the target model takes static input, i.e., an attacker can ...
Yuan Gong 0001 +3 more
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Adversarial Attacks on Human Vision
CoRR, 2022 This article presents an introduction to visual attention retargeting, its connection to visual saliency, the challenges associated with it, and ideas for how it can be approached. The difficulty of attention retargeting as a saliency inversion problem lies in the lack of one-to-one mapping between saliency and the image domain, in addition to the ...
Victor A. Mateescu, Ivan V. Bajic
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