Jun 6, 2023 · We compare query-based attacks by their effectiveness and efficiency; based on this comparison we develop recommendations for how to design and ...
Model-stealing attacks are emerging as a severe threat to AI-based services because an adversary can create models that duplicate the functionality of the ...
Missing: your Machine
A second, and even less detectable theft is the extraction of your ML model from your application for use in the hacker's application. If this is a direct ...
... the biggest challenges when deploying machine learning models in the real world. ... effectively by identifying a shadow model similar to the target model ...
Model extraction attacks, aka model stealing attacks, are used to extract the parameters from the target model. Ideally, the adversary will be able to steal ...
May 21, 2020 · In a previous blog post, we talked about model extraction attacks as a way for someone to steal a model that's been made available to query. In ...
Missing: your | Show results with:your
Abstract: Machine learning architectures are readily available, but obtaining the high quality labeled data for training is costly. Pre-trained models ...
Missing: Efficiently | Show results with:Efficiently
The widespread deployment of deep neural networks (DNNs) [1], [2], [3] has catalyzed the advent of Machine Learning as a Service (MLaaS), wherein models are ...
Sep 30, 2016 · Wired magazine just published an article with the interesting title How to Steal an AI, where the author explores the topic of reverse ...
Abstract: Stealing trained machine learning (ML) models is a new and growing concern due to the model's development cost. Existing work on ML model ...