References
- Krizhevsky, A., Sutskever, I., and Hinton, G. E., "Imagenet classification with deep convolutional neural networks," in Proc. Adv. Neural Inf. Process. Syst. (NIPS), pp. 1097-1105, 2012.
- He, K., Zhang, X., Ren, S., and Sun, J., "Deep residual learning for image recognition," in Proc. IEEE Conf. Comput. Vision Pattern Recognition (CVPR), pp. 770-778, 2016.
- Papernot, N., McDaniel, P., Jha, S., Fedrikson, M., Celik, Z.B., Swami, A., "The limitation of deep learning in adversarial settings," in Proc. IEEE European Symp. Security & Privacy (ESSP), 2016.
- Goodfellow, I. J., Shlens, J., and Szegedy, C., "Explaining and harnessing adversarial examples," in Proc. Int. Conf. Learning Representations (ICLR), 2015.
- Szegedy, C., Zaremba, W., Sutskever, I., Bruna, J., Erhan, D., Goodfellow, I., and Fergus. R., "Intriguing properties of neural networks," in Proc. Int. Conf. Learning Representations (ICLR), 2014.
- Nguyen, A., Yosinski, J., and Clune. J., "Deep neural networks are easily fooled: High confidence predictions for unrecognizable images," in Proc. IEEE Conf. Comput. Vision Pattern Recognition (CVPR), 2015.
- Schunter, M., "Vehicle to cloud - Emerging security research challenges for intelligent vehicles," in Proc. Embedded Security in Cars (ESCAR), 2017.