Results 31 to 40 of about 353,439 (278)
Towards Measuring Adversarial Twitter Interactions against Candidates in the US Midterm Elections
, 2020 Adversarial interactions against politicians on social media such as Twitter have significant impact on society. In particular they disrupt substantive political discussions online, and may discourage people from seeking public office.
Hua, Yiqing +2 more
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Сибирское юридическое обозрение, 2020 The article gives a brief historical description of the role of the court in the collection of evidence. The arguments in favor of strengthening the role of the court for the recovery of evidence are presented. In particular, the Author substantiates the
A. D. Dzumatov
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Applied Sciences, 2023 In this paper, we propose an advanced method for adversarial training that focuses on leveraging the underlying structure of adversarial perturbation distributions. Unlike conventional adversarial training techniques that consider adversarial examples in
Bader Rasheed +2 more
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Generating Adversarial Examples with Adversarial Networks [PDF]
Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence, 2018 Deep neural networks (DNNs) have been found to be vulnerable to adversarial examples resulting from adding small-magnitude perturbations to inputs. Such adversarial examples can mislead DNNs to produce adversary-selected results. Different attack strategies have been proposed to generate adversarial examples, but how to produce them with high ...
Xiao, Chaowei +5 more
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Universal Adversarial Perturbations [PDF]
2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR), 2017 Given a state-of-the-art deep neural network classifier, we show the existence of a universal (image-agnostic) and very small perturbation vector that causes natural images to be misclassified with high probability. We propose a systematic algorithm for computing universal perturbations, and show that state-of-the-art deep neural networks are highly ...
Moosavi-Dezfooli, Seyed-Mohsen +3 more
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Frontiers in Neurorobotics, 2018 Many real-world decision-making problems involve multiple conflicting objectives that can not be optimized simultaneously without a compromise. Such problems are known as multi-objective Markov decision processes and they constitute a significant ...
Sherif Abdelfattah +2 more
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Adversarial smoothed analysis [PDF]
Journal of Complexity, 2010 The purpose of this note is to extend the results on uniform smoothed analysis of condition numbers from \cite{BuCuLo:07} to the case where the perturbation follows a radially symmetric probability distribution. In particular, we will show that the bounds derived in \cite{BuCuLo:07} still hold in the case of distributions whose density has a ...
Cucker, Felipe +2 more
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Stochastic-Adversarial Channels: Online Adversaries With Feedback Snooping [PDF]
2021 IEEE International Symposium on Information Theory (ISIT), 2021 Extended draft of the conference paper with the same title submitted to the IEEE International Symposium on Information Theory (ISIT ...
Suresh, Vinayak +2 more
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Entropy, 2022 Deep neural networks in the area of information security are facing a severe threat from adversarial examples (AEs). Existing methods of AE generation use two optimization models: (1) taking the successful attack as the objective function and limiting perturbations as the constraint; (2) taking the minimum of adversarial perturbations as the target and
Zhenyu Du, Fangzheng Liu, Xuehu Yan
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Targeted Universal Adversarial Examples for Remote Sensing
Remote Sensing, 2022 Researchers are focusing on the vulnerabilities of deep learning models for remote sensing; various attack methods have been proposed, including universal adversarial examples.
Tao Bai, Hao Wang, Bihan Wen
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