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Keyword

adversarial examples

Description: Adversarial examples are inputs deliberately or inadvertently modified to cause machine-learning models to make incorrect predictions.
Wikidata ID: wiki/Q115727235
OpenAlex ID: keywords/adversarial-examples
Explaining and Harnessing Adversarial Examples
2014 · Goodfellow, Ian J., Shlens, Jonathon, et al. · arXiv (Cornell University) · 10,377
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Towards Evaluating the Robustness of Neural Networks
2017 · Nicholas Carlini, David Wagner · Proceedings - IEEE Symposium on Security and Privacy/Proceedings of the ... IEEE Symposium on Security and Privacy · 8,831
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Adversarial Examples in the Physical World
2018 · Alexey Kurakin, Ian J. Goodfellow, et al. · Chapman & Hall/CRC eBooks · 5,369
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Towards Deep Learning Models Resistant to Adversarial Attacks
2017 · Madry, Aleksander, Makelov, Aleksandar, et al. · arXiv (Cornell University) · 4,069
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The Limitations of Deep Learning in Adversarial Settings
2016 · Nicolas Papernot, Patrick McDaniel, et al. · IEEE European Symposium on Security and Privacy · 3,981
Practical Black-Box Attacks against Machine Learning
2017 · Nicolas Papernot, Patrick McDaniel, et al. · ACM Asia Conference on Computer and Communications Security (ASIA CCS) · 3,488
Deep neural networks are easily fooled: High confidence predictions for unrecognizable images
2015 · Anh Nguyen, Jason Yosinski, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 3,256
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Boosting Adversarial Attacks with Momentum
2018 · Yinpeng Dong, Fangzhou Liao, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 3,139
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Adversarial Machine Learning at Scale
2016 · Kurakin, Alexey, Goodfellow, Ian, et al. · arXiv (Cornell University) · 2,326
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Ensemble Adversarial Training: Attacks and Defenses
2017 · Tramèr, Florian, Kurakin, Alexey, et al. · arXiv (Cornell University) · 2,177
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Obfuscated Gradients Give a False Sense of Security: Circumventing Defenses to Adversarial Examples
2018 · Athalye, Anish, Carlini, Nicholas, et al. · arXiv (Cornell University) · 2,171
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Robust Physical-World Attacks on Deep Learning Visual Classification
2018 · Kevin Eykholt, Ivan Evtimov, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 2,164
Feature Squeezing: Detecting Adversarial Examples in Deep Neural Networks
2018 · Weilin Xu, David Evans, et al. · Network and Distributed System Security Symposium · 1,855
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ZOO
2017 · Pin-Yu Chen, Huan Zhang, et al. · ACM Workshop on Artificial Intelligence and Security (AISec) · 1,760
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Adversarial Examples: Attacks and Defenses for Deep Learning
2019 · Xiaoyong Yuan, Pan He, et al. · IEEE Transactions on Neural Networks and Learning Systems · 1,727
Theoretically Principled Trade-off between Robustness and Accuracy
2019 · Zhang, Hongyang, Yu, Yaodong, et al. · arXiv (Cornell University) · 1,488
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Wild patterns: Ten years after the rise of adversarial machine learning
2018 · Battista Biggio, Fabio Roli · Pattern Recognition · 1,431
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Adversarial Examples for Evaluating Reading Comprehension Systems
2017 · Robin Jia, Percy Liang · Conference on Empirical Methods in Natural Language Processing (EMNLP) · 1,371
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Adversarial Examples Are Not Easily Detected
2017 · Nicholas Carlini, David Wagner · ACM Workshop on Artificial Intelligence and Security (AISec) · 1,344
Improving Transferability of Adversarial Examples With Input Diversity
2019 · Cihang Xie, Zhishuai Zhang, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 1,340
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Transferability in Machine Learning: from Phenomena to Black-Box Attacks using Adversarial Samples
2016 · Papernot, Nicolas, McDaniel, Patrick, et al. · arXiv (Cornell University) · 1,326
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Delving into Transferable Adversarial Examples and Black-box Attacks
2016 · Liu, Yanpei, Chen, Xinyun, et al. · arXiv (Cornell University) · 1,310
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HiDDeN: Hiding Data With Deep Networks
2018 · Jiren Zhu, Russell Kaplan, et al. · Lecture notes in computer science · 1,177
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Natural Adversarial Examples
2021 · Dan Hendrycks, Kevin Zhao, et al. · IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings - IEEE Computer Society Conference on Computer Vision and Pattern Recognition/Proceedings · 1,052
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Countering Adversarial Images using Input Transformations
2017 · Guo, Chuan, Rana, Mayank, et al. · arXiv (Cornell University) · 1,021
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Works count: 9,119
Citation count: 227,600
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