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.

... a. Page 3. Stealing Machine Learning Models: Attacks and Countermeasures for Generative Adversarial Networks. ACSAC '21, December 6–10, 2021, Virtual Event ...

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 ...

Creating good ML models, however, can be expensive and the used data is often sensitive. Recently, Secure Multi-Party Computation (SMPC) protocols for MLaaS ...

Given these practices, we show simple, efficient attacks that extract target ML models with near-perfect fidelity for popular model classes including logistic ...

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.

Jun 6, 2023 · There are two main approaches for protecting a Machine Learning model against a model stealing attack: attack detection [8] and attack ...

This paper introduces GuardNet, an innovative model stealing detection method. By combining boundary features with inter-sample distance features, GuardNet ...

The simpler the confidential model, the easier to extract the model. ○ Active Learning and Self-supervised Learning makes model extraction attack even easier ...