Hint: Stay until the end of the video for an adversarial attack compilation!
🤔 Ever wondered what adversarial attacks are? What FGSM, the Fast Gradient Sign method, is? What the difference between Adversarial Machine Learning and Generative Adversarial Networks is? If yes, you have found the right video for you!
Outline:
* 00:00 Difference between GANs and Adversarial ML
* 01:04 Noise Attack
* 01:52 Fast Gradient Sign Method (FGSM)
* 03:53 Targeted vs Untargeted
* 04:53 White box vs Black box
* 05:38 Adversarial examples
* 06:32 Defenses against adversarial attacks
* 08:46 Aversarial examples COMPILATION
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🔥 Optionally, pay us a coffee to boost our Coffee Bean production! ☕
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For all the juicy details about the topic, check out this video @Stanford University School of Engineering : https://www.youtube.com/watch?v=CIfsB_EYsVI
📄 Goodfellow, Ian J., Jonathon Shlens, and Christian Szegedy. "Explaining and harnessing adversarial examples." arXiv preprint arXiv:1412.6572 (2014). https://arxiv.org/pdf/1412.6572.pdf
📄 Thys, Simen, Wiebe Van Ranst, and Toon Goedemé. "Fooling automated surveillance cameras: adversarial patches to attack person detection." In Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition Workshops, pp. 0-0. 2019. https://arxiv.org/pdf/1904.08653.pdf
📄 Belinkov, Yonatan, and Yonatan Bisk. "Synthetic and natural noise both break neural machine translation." arXiv preprint arXiv:1711.02173 (2017). https://arxiv.org/pdf/1711.02173.pdf
🔗 Links:
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Video contains emojis designed by OpenMoji – the open-source emoji and icon project. License: CC BY-SA 4.0
00:00 Difference between GANs and Adversarial ML
01:04 Noise Attack
01:52 Fast Gradient Sign Method (FGSM)
03:53 Targeted vs Untargeted
04:53 White box vs Black box
05:38 Adversarial examples
06:32 Defenses against adversarial attacks
08:46 Aversarial examples COMPILATION
