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MultiRobustBench: Benchmarking Robustness Against Multiple Attacks.

, , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 6760-6785. PMLR, (2023)

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Better the Devil you Know: An Analysis of Evasion Attacks using Out-of-Distribution Adversarial Examples., , , , , , and . CoRR, (2019)MultiRobustBench: Benchmarking Robustness Against Multiple Attacks., , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 6760-6785. PMLR, (2023)Uncovering Adversarial Risks of Test-Time Adaptation., , , , , , and . ICML, volume 202 of Proceedings of Machine Learning Research, page 37456-37495. PMLR, (2023)A Light Recipe to Train Robust Vision Transformers., , and . SaTML, page 225-253. IEEE, (2023)TV-PUF: A Fast Lightweight Analog Physical Unclonable Function., and . iNIS, page 182-186. IEEE, (2016)Beyond $L_p$ Norms: Delving Deeper into Robustness to Physical Image Transformations., , and . MILCOM, page 189-196. IEEE, (2021)PatchGuard: A Provably Robust Defense against Adversarial Patches via Small Receptive Fields and Masking., , , and . USENIX Security Symposium, page 2237-2254. USENIX Association, (2021)Extracting Training Data from Diffusion Models., , , , , , , , and . USENIX Security Symposium, page 5253-5270. USENIX Association, (2023)RobustBench: a standardized adversarial robustness benchmark., , , , , , , and . NeurIPS Datasets and Benchmarks, (2021)Not All Pixels are Born Equal: An Analysis of Evasion Attacks under Locality Constraints., , , , , and . CCS, page 2285-2287. ACM, (2018)