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Enhancing Proof-of-Learning Security Against Spoofing Attacks Using Model Watermarking

Ural, Ozgur

… the computational effort invested in training ML models, thereby certifying the authenticity and reproducibility of the training process. Yet PoL, when deployed in isolation, remains vulnerable to sophisticated spoofing attacks that manipulate its subset-verification pathways and tolerance …

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