10 citations · 10 across the 2 of their papers we have counts for
3 papers
The Coding Limits of Robust Watermarking for Generative Models
Danilo Francati, Yevin Nikhel Goonatilake, Shubham Pawar +2
We study a basic question about cryptographic watermarking for generative models: how reliable can a watermark remain when an adversary is allowed to corrupt the encoded signal? To…
Watermarks in the Sand: Impossibility of Strong Watermarking for Generative Models
Hanlin Zhang, Benjamin L. Edelman, Danilo Francati +3
Watermarking generative models consists of planting a statistical signal (watermark) in a model's output so that it can be later verified that the output was generated by the given…
Eluding Secure Aggregation in Federated Learning via Model Inconsistency
Dario Pasquini, Danilo Francati, Giuseppe Ateniese
Secure aggregation is a cryptographic protocol that securely computes the aggregation of its inputs. It is pivotal in keeping model updates private in federated learning. Indeed, t…