May 7, 2024, 4:12 a.m. | Nicholas Carlini, Matthew Jagielski, Christopher A. Choquette-Choo, Daniel Paleka, Will Pearce, Hyrum Anderson, Andreas Terzis, Kurt Thomas, Florian T

cs.CR updates on arXiv.org arxiv.org

arXiv:2302.10149v2 Announce Type: replace
Abstract: Deep learning models are often trained on distributed, web-scale datasets crawled from the internet. In this paper, we introduce two new dataset poisoning attacks that intentionally introduce malicious examples to a model's performance. Our attacks are immediately practical and could, today, poison 10 popular datasets. Our first attack, split-view poisoning, exploits the mutable nature of internet content to ensure a dataset annotator's initial view of the dataset differs from the view downloaded by subsequent clients. …

arxiv attack attacks crawled cs.cr cs.lg dataset datasets deep learning distributed examples internet malicious performance poisoning poisoning attacks popular scale today training web

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