1 citations · 1 across the 3 of their papers we have counts for
3 papers
Verifiable Unlearning on Edge
Mohammad M Maheri, Alex Davidson, Hamed Haddadi
Machine learning providers commonly distribute global models to edge devices, which subsequently personalize these models using local data. However, issues such as copyright infrin…
TeleSparse: Practical Privacy-Preserving Verification of Deep Neural Networks
Mohammad M Maheri, Hamed Haddadi, Alex Davidson
Verification of the integrity of deep learning inference is crucial for understanding whether a model is being applied correctly. However, such verification typically requires acce…
GuaranTEE: Towards Attestable and Private ML with CCA
Sandra Siby, Sina Abdollahi, Mohammad Maheri +2
Machine-learning (ML) models are increasingly being deployed on edge devices to provide a variety of services. However, their deployment is accompanied by challenges in model priva…