13 citations · 39 across the 25 of their papers we have counts for
9 papers · 1 filter
Proofs of Ownership for Machine Learning Models
Ran Canetti, Shafi Goldwasser, Or Zamir
With the increasing adoption of Machine Learning, protecting model ownership has become an essential challenge. We initiate a formal study of Proof of Ownership for machine learnin…
Efficient Public Verification of Private ML via Regularization
Zoë Ruha Bell, Anvith Thudi, Olive Franzese-McLaughlin +2
Training with differential privacy (DP) guarantees dataset members that they cannot be identified by users of the released model. However, those data providers, and, in general, th…
WhAM: Towards A Translative Model of Sperm Whale Vocalization
Orr Paradise, Pranav Muralikrishnan, Liangyuan Chen +6
Sperm whales communicate in short sequences of clicks known as codas. We present WhAM (Whale Acoustics Model), the first transformer-based model capable of generating synthetic spe…
A Cryptographic Perspective on Mitigation vs. Detection in Machine Learning
Greg Gluch, Shafi Goldwasser
In this paper, we initiate a cryptographically inspired theoretical study of detection versus mitigation of adversarial inputs produced by attackers on Machine Learning algorithms…
Learning Randomized Reductions
Ferhat Erata, Orr Paradise, Thanos Typaldos +4
Randomized self-reductions (RSRs) express using evaluated at random correlated points, enabling self-correcting programs, instance-hiding protocols, and applications in…
Oblivious Defense in ML Models: Backdoor Removal without Detection
Shafi Goldwasser, Jonathan Shafer, Neekon Vafa +1
As society grows more reliant on machine learning, ensuring the security of machine learning systems against sophisticated attacks becomes a pressing concern. A recent result of Go…