Results 31 to 40 of about 243,531 (318)
Exploring Diverse Feature Extractions for Adversarial Audio Detection
IEEE Access, 2023 Although deep learning models have exhibited excellent performance in various domains, recent studies have discovered that they are highly vulnerable to adversarial attacks.
Yujin Choi +3 more
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Adversarial Examples and Metrics
CoRR, 2020 25 pages, 1 figure, under submission, fixe typos from previous ...
Nico Döttling +3 more
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Unrestricted Adversarial Examples
CoRR, 2018 We introduce a two-player contest for evaluating the safety and robustness of machine learning systems, with a large prize pool. Unlike most prior work in ML robustness, which studies norm-constrained adversaries, we shift our focus to unconstrained adversaries.
Tom B. Brown +5 more
openaire +2 more sources
“Adversarial Examples” for Proof-of-Learning
2022 IEEE Symposium on Security and Privacy (SP), 2022 To appear in the 43rd IEEE Symposium on Security and ...
Rui Zhang 0118 +5 more
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Improving Adversarial Robustness via Attention and Adversarial Logit Pairing
Frontiers in Artificial Intelligence, 2022 Though deep neural networks have achieved the state of the art performance in visual classification, recent studies have shown that they are all vulnerable to the attack of adversarial examples. In this paper, we develop improved techniques for defending
Xingjian Li +4 more
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Survey of Image Adversarial Example Defense Techniques [PDF]
Jisuanji kexue yu tansuo, 2023 The rapid and extensive growth of artificial intelligence introduces new security challenges. The generation and defense of adversarial examples for deep neural networks is one of the hot spots.
LIU Ruiqi, LI Hu, WANG Dongxia, ZHAO Chongyang, LI Boyu
doaj +1 more source
Adversarial Examples for Generative Models [PDF]
2018 IEEE Security and Privacy Workshops (SPW), 2018 We explore methods of producing adversarial examples on deep generative models such as the variational autoencoder (VAE) and the VAE-GAN. Deep learning architectures are known to be vulnerable to adversarial examples, but previous work has focused on the application of adversarial examples to classification tasks.
Jernej Kos, Ian Fischer, Dawn Song
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Adversarial examples in remote sensing [PDF]
Proceedings of the 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems, 2018 This paper considers attacks against machine learning algorithms used in remote sensing applications, a domain that presents a suite of challenges that are not fully addressed by current research focused on natural image data such as ImageNet. In particular, we present a new study of adversarial examples in the context of satellite image classification
Wojciech Czaja +4 more
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A Robust Adversarial Example Attack Based on Video Augmentation
Applied Sciences, 2023 Despite the success of learning-based systems, recent studies have highlighted video adversarial examples as a ubiquitous threat to state-of-the-art video classification systems.
Mingyong Yin +3 more
doaj +1 more source
Not all adversarial examples require a complex defense : identifying over-optimized adversarial examples with IQR-based logit thresholding [PDF]
, 2019 Detecting adversarial examples currently stands as one of the biggest challenges in the field of deep learning. Adversarial attacks, which produce adversarial examples, increase the prediction likelihood of a target class for a particular data point ...
De Neve, Wesley +2 more
core +2 more sources