We show that it is possible to extract a highly accurate model using only 854 queries with the estimated cost of $0.09 on the Amazon ML platform.
We use our framework to examine the accuracy of our attacks on ML models trained on publicly available state-of-the-art datasets, as well as their computation ...
Nov 15, 2019 · An adversary trying to steal the model also will typically have some large dataset of points they want to classify (they just don't want to pay ...
Machine Learning as a Service (MLaaS) is a growing paradigm in the Machine Learning (ML) landscape. More and more ML models are being uploaded to the cloud ...
We show simple, efficient attacks that extract target ML models with near-perfect fidelity for popular model classes.
Jun 6, 2023 · There are two main approaches for protecting a Machine Learning model against a model stealing attack: attack detection [8] and attack ...
Model stealing is a type of a threat in which an adversary duplicates a machine learning model without direct access to its parameters or data.
In recent years, “Machine Learning as a Service” (MLaaS) has become a cost-effective alter- native to learning models on-site. ... Stealing machine learning.
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A multi-faceted approach to model protection, combining robust licensing, encryption, and sophisticated software protection tools.
May 20, 2024 · Significant efforts have been devoted to developing model-stealing attacks that extract models trained on images and texts. However, little ...
