4 papers · 1 filter
AgenTEE: Confidential LLM Agent Execution on Edge Devices
Sina Abdollahi, Mohammad M Maheri, Javad Forough +5
Large Language Model (LLM) agents provide powerful automation capabilities, but they also create a substantially broader attack surface than traditional applications due to their t…
ZK-APEX: Zero-Knowledge Approximate Personalized Unlearning with Executable Proofs
Mohammad M Maheri, Sunil Cotterill, Alex Davidson +1
Machine unlearning aims to remove the influence of specific data points from a trained model to satisfy privacy, copyright, and safety requirements. In real deployments, providers…
An Early Experience with Confidential Computing Architecture for On-Device Model Protection
Sina Abdollahi, Mohammad Maheri, Sandra Siby +2
Deploying machine learning (ML) models on user devices can improve privacy (by keeping data local) and reduce inference latency. Trusted Execution Environments (TEEs) are a practic…
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…