The DOI matches its Crossref record; 51 of the 51 references it cites were found in a registry or an index.
Square Attack: A Query-Efficient Black-Box Adversarial Attack via Random Search
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Cites
Boyd, S., & Vandenberghe, L. (2004) · doi:10.1017/cbo9780511804441 · Cited by 56,601
Distillation as a Defense to Adversarial Perturbations Against Deep Neural Networks
Papernot, N., McDaniel, P., Wu, X., Jha, S., & Swami, A. (2016) · 2016 IEEE Symposium on Security and Privacy (SP) · doi:10.1109/sp.2016.41 · Cited by 2,982
One Pixel Attack for Fooling Deep Neural Networks
Su, J., Vargas, D. V., & Sakurai, K. (2019) · IEEE Transactions on Evolutionary Computation · doi:10.1109/tevc.2019.2890858 · Cited by 2,406
Obfuscated gradients give a false sense of security: Circumventing defenses to adversarial examples
Athalye, A., Carlini, N., & Wagner, D. (2018) · arXiv · doi:10.48550/arxiv.1802.00420 · Cited by 2,172
Threat of Adversarial Attacks on Deep Learning in Computer Vision: A Survey
Akhtar, N., & Mian, A. (2018) · IEEE Access · doi:10.1109/access.2018.2807385 · Cited by 2,021
Yu, F., Koltun, V., & Funkhouser, T. (2017) · 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR) · doi:10.1109/cvpr.2017.75 · Cited by 1,804
Chen, P.-Y., Zhang, H., Sharma, Y., Yi, J., & Hsieh, C.-J. (2017) · Proceedings of the 10th ACM Workshop on Artificial Intelligence and Security · doi:10.1145/3128572.3140448 · Cited by 1,656
Theoretically principled trade-off between robustness and accuracy
Zhang, H., Yu, Y., Jiao, J., Xing, E. P., Ghaoui, L. E., & Jordan, M. I. (2019) · arXiv · doi:10.48550/arxiv.1901.08573 · Cited by 1,560
Wild patterns: Ten years after the rise of adversarial machine learning
Biggio, B., & Roli, F. (2018) · Pattern Recognition · doi:10.1016/j.patcog.2018.07.023 · Cited by 1,409
Problem complexity and method efficiency in optimization
(1984) · Mathematics and Computers in Simulation · doi:10.1016/0378-4754(84)90101-0 · Cited by 1,329
Cited by
Boosting Fast Adversarial Training With Learnable Adversarial Initialization
Jia, X., Zhang, Y., Wu, B., Wang, J., & Cao, X. (2022) · IEEE Transactions on Image Processing · doi:10.1109/tip.2022.3184255 · Cited by 69
Security and Privacy Issues in Deep Learning
Bae, H., Jang, J., Jung, D., Jang, H., Ha, H., Lee, H., & Yoon, S. (2018) · arXiv · doi:10.48550/arxiv.1807.11655 · Cited by 56
Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks
Croce, F., & Hein, M. (2020) · arXiv · doi:10.48550/arxiv.2003.01690
Self-citation
Metadata
- Authors
- Andriushchenko, M., Croce, F., Flammarion, N., & Hein, M.
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2020
- Pages
- 484-501
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2991240978
- Cited by
- 800
- References
- 51
- FWCI
- 38.70
- Type
- conference paper
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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