CanSecWest 2019 | 如何用AI“欺骗”AI？

Zhou, W., Hou, X., Chen, Y., Tang, M., Huang, X., Gan, X., & Yang, Y. (2018). Transferable Adversarial Perturbations. In Proceedings of the European Conference on Computer Vision (ECCV) (pp. 452-467).

https://console.aws.amazon.com/rekognition/home?region=us-east-1#/celebrity-detection

https://azure.microsoft.com/en-us/services/cognitive-services/computer-vision/

Ren, S., He, K., Girshick, R., & Sun, J. (2015). Faster r-cnn: Towards real-time object detection with region proposal networks. In Advances in neural information processing systems (pp. 91-99).

https://cloud.google.com/vision/

Papernot, N., McDaniel, P., Wu, X., Jha, S., & Swami, A. (2016, May). Distillation as a defense to adversarial perturbations against deep neural networks. In 2016 IEEE Symposium on Security and Privacy (SP) (pp. 582-597). IEEE.

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