The Good, the Bad and the Ugly: Meta-Analysis of Watermarks, Transferable Attacks and Adversarial Defenses

October 11, 2024 ยท Declared Dead ยท ๐Ÿ› ICML 2024

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Authors Grzegorz Gล‚uch, Berkant Turan, Sai Ganesh Nagarajan, Sebastian Pokutta arXiv ID 2410.08864 Category cs.LG: Machine Learning Cross-listed cs.AI, cs.CR Citations 0 Venue ICML 2024 Last Checked 5 months ago
Abstract
We formalize and analyze the trade-off between backdoor-based watermarks and adversarial defenses, framing it as an interactive protocol between a verifier and a prover. While previous works have primarily focused on this trade-off, our analysis extends it by identifying transferable attacks as a third, counterintuitive, but necessary option. Our main result shows that for all learning tasks, at least one of the three exists: a watermark, an adversarial defense, or a transferable attack. By transferable attack, we refer to an efficient algorithm that generates queries indistinguishable from the data distribution and capable of fooling all efficient defenders. Using cryptographic techniques, specifically fully homomorphic encryption, we construct a transferable attack and prove its necessity in this trade-off. Finally, we show that tasks of bounded VC-dimension allow adversarial defenses against all attackers, while a subclass allows watermarks secure against fast adversaries.
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