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Blacklight: Scalable Defense for Neural Networks against Query-Based Black-Box Attacks.

, , , , , and . USENIX Security Symposium, page 2117-2134. USENIX Association, (2022)

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Data Isotopes for Data Provenance in DNNs., , , and . CoRR, (2022)Fawkes: Protecting Privacy against Unauthorized Deep Learning Models., , , , , and . USENIX Security Symposium, page 1589-1604. USENIX Association, (2020)Glaze: Protecting Artists from Style Mimicry by Text-to-Image Models., , , , , and . USENIX Security Symposium, page 2187-2204. USENIX Association, (2023)Fawkes: Protecting Personal Privacy against Unauthorized Deep Learning Models., , , , , and . CoRR, (2020)Data Isotopes for Data Provenance in DNNs., , , and . Proc. Priv. Enhancing Technol., 2024 (1): 413-429 (January 2024)Blacklight: Defending Black-Box Adversarial Attacks on Deep Neural Networks., , , , , and . CoRR, (2020)Gotta Catch'Em All: Using Honeypots to Catch Adversarial Attacks on Neural Networks., , , , , and . CCS, page 67-83. ACM, (2020)SalsaPicante: A Machine Learning Attack on LWE with Binary Secrets., , , , , , and . CCS, page 2606-2620. ACM, (2023)SoK: Anti-Facial Recognition Technology., , , and . CoRR, (2021)SALSA FRESCA: Angular Embeddings and Pre-Training for ML Attacks on Learning With Errors., , , , , , and . IACR Cryptol. ePrint Arch., (2024)