对抗神经网络的参考文献有哪些

以下是对抗神经网络的参考文献：

1. Goodfellow, I., Shlens, J., & Szegedy, C. (2014). Explaining and Harnessing Adversarial Examples.

2. Papernot, N., McDaniel, P., Jha, S., Fredrikson, M., Celik, Z. B., & Swami, A. (2016). The limitations of deep learning in adversarial settings.

3. Kurakin, A., Goodfellow, I., & Bengio, S. (2016). Adversarial examples in the physical world.

4. Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I., & Fergus, R. (2013). Intriguing properties of neural networks.

5. Carlini, N., & Wagner, D. (2017). Towards evaluating the robustness of neural networks.

6. Nguyen, A., Yosinski, J., & Clune, J. (2015). Deep neural networks are easily fooled: High confidence predictions for unrecognizable images.

7. Madry, A., Makelov, A., Schmidt, L., Tsipras, D., & Vladu, A. (2018). Towards deep learning models resistant to adversarial attacks.

8. Brown, T. B., Mané, D., Roy, A., Abadi, M., & Gilmer, J. (2017). Adversarial patch.

9. Moosavi-Dezfooli, S. M., Fawzi, A., & Frossard, P. (2016). Deepfool: a simple and accurate method to fool deep neural networks.

10. Huang, X., Li, Y., Poursaeed, O., Hopcroft, J., & Belongie, S. (2017). Adversarial attacks on neural network policies.