Cloud service providers, including Google, Amazon, and Alibaba, have now launched machinelearning-as-a-service (MLaaS) platforms, allowing clients to access sophisticated …
Abstract Data-Free Model Extraction (DFME) aims to clone a black-box model without knowing its original training data distribution, making it much easier for attackers to steal …
As a promising service, Machine Learning as a Service (MLaaS) provides personalized inference functions for clients through paid APIs. Nevertheless, it is vulnerable to model …
Machine learning models are vulnerable to simple model stealing attacks if the adversary can obtain output labels for chosen inputs. To protect against these attacks, it has been …
Z Li, C Shi, Y Pu, X Zhang, Y Li, J Li, S Ji - arXiv preprint arXiv:2312.14677, 2023 - arxiv.org
The widespread use of deep learning technology across various industries has made deep neural network models highly valuable and, as a result, attractive targets for potential …
Despite the broad application of Machine Learning models as a Service (MLaaS), they are vulnerable to model stealing attacks. These attacks can replicate the model functionality by …
While deep learning models have shown significant performance across various domains, their deployment needs extensive resources and advanced computing infrastructure. As a …
T Miura, T Shibahara, N Yanai - Proceedings of the 2nd ACM Workshop …, 2024 - dl.acm.org
Explainable AI encourages machine learning applications in the real world, whereas data- free model extraction attacks (DFME), in which an adversary steals a trained machine …
In model extraction attacks, adversaries can steal a machine learning model exposed via a public API by repeatedly querying it and adjusting their own model based on obtained …