Funder
Major Program of the National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Subject
Computer Networks and Communications,Hardware and Architecture,Media Technology,Software
Reference47 articles.
1. Carlini N, Wagner D (2017) Towards evaluating the robustness of neural networks. In: 2017 IEEE symposium on security and privacy (SP), pp 39–57, https://doi.org/10.1109/SP.2017.49
2. Chakraborty A, Alam M, Dey V et al (2021) A survey on adversarial attacks and defences. CAAI Trans Intell Technol 6(1):25–45. https://doi.org/10.1049/cit2.12028
3. Chen T, Zhang Z, Wang P et al (2022) Sparsity winning twice: Better robust generalization from more efficient training. In: The tenth international conference on learning representations, ICLR
4. Croce F, Hein M (2020) Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks. In: Proceedings of the 37th international conference on machine learning, ICML, pp 2206–2216 http://proceedings.mlr.press/v119/croce20b.html
5. Esmaeili B, Akhavanpour A, Sabokrou M (2021) Maximising robustness and diversity for improving the deep neural network safety. Electron Lett 57(3):116–118. https://doi.org/10.1049/ell2.12070