Readings on: adversarial machine learning

Main reading for Thursday, April 4th: Jonathan Prokos, Neil Fendley, Matthew Green, Roei Schuster, Eran Tromer, Tushar Jois, and Yinzhi Cao. “Squint Hard Enough: Attacking Perceptual Hashing with Adversarial Machine Learning”. In USENIX Security Symposium, August 2023.
[USENIX]

Candidate main reading: Shibo Zhang, Yushi Cheng, Wenjun Zhu, Xiaoyu Ji, and Wenyuan Xu. “CAPatch: Physical Adversarial Patch against Image Captioning Systems”. In USENIX Security Symposium, August 2023.
[USENIX]

Candidate main reading: Keane Lucas, Samruddhi Pai, Weiran Lin, Lujo Bauer, Michael K. Reiter, and Mahmood Sharif. “Adversarial Training for Raw-Binary Malware Classifiers ”. In USENIX Security Symposium, August 2023.
[USENIX]

Main reading for Tuesday, April 2nd: Shawn Shan, Jenna Cryan, Emily Wenger, Haitao Zheng, Rana Hanocka, and Ben Y. Zhao. “Glaze: Protecting Artists from Style Mimicry by Text-to-Image Models”. In USENIX Security Symposium, August 2023.
[USENIX]

Candidate main reading: Nicholas Carlini, Milad Nasr, Christopher A. Choquette-Choo, Matthew Jagielski, Irena Gao, Anas Awadalla, Pang Wei Koh, Daphne Ippolito, Katherine Lee, Florian Tramer, and Ludwig Schmidt. “Are aligned neural networks adversarially aligned?” In Neural Information Processing Systems (NeurIPS), December 2023.
[arXiv]