Results 31 to 40 of about 177,286 (215)
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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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 attacks and defenses in deep learning
网络与信息安全学报, 2020 The adversarial example is a modified image that is added imperceptible perturbations, which can make deep neural networks decide wrongly. The adversarial examples seriously threaten the availability of the system and bring great security risks to the ...
LIU Ximeng +2 more
doaj +3 more sources
A Multimodal Adversarial Attack Framework Based on Local and Random Search Algorithms
International Journal of Computational Intelligence Systems, 2021 Although many problems in computer vision and natural language processing have made breakthrough progress with neural networks, adversarial attack is a serious potential problem in many neural network- based applications.
Zibo Yi, Jie Yu, Yusong Tan, Qingbo Wu
doaj +1 more source
Impact of adversarial examples on deep learning models for biomedical image segmentation [PDF]
, 2019 Deep learning models, which are increasingly being used in the field of medical image analysis, come with a major security risk, namely, their vulnerability to adversarial examples.
C Pena-Betancor +3 more
core +4 more sources
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
openaire +2 more sources
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
Instance attack: an explanation-based vulnerability analysis framework against DNNs for malware detection [PDF]
PeerJ Computer Science, 2023 Deep neural networks (DNNs) are increasingly being used in malware detection and their robustness has been widely discussed. Conventionally, the development of an adversarial example generation scheme for DNNs involves either detailed knowledge ...
Ruijin Sun +6 more
doaj +2 more sources
Are adversarial examples inevitable?
CoRR, 2018 ISBN:978-1-7138-7273 ...
Shafahi, Ali +4 more
openaire +4 more sources