Model extraction
18 papers with code • 0 benchmarks • 1 datasets
Benchmarks
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Most implemented papers
Stealing Machine Learning Models via Prediction APIs
In such attacks, an adversary with black-box access, but no prior knowledge of an ML model's parameters or training data, aims to duplicate the functionality of (i. e., "steal") the model.
An Approach for Process Model Extraction By Multi-Grained Text Classification
qianc62/MGTC
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Process model extraction (PME) is a recently emerged interdiscipline between natural language processing (NLP) and business process management (BPM), which aims to extract process models from textual descriptions.
DAWN: Dynamic Adversarial Watermarking of Neural Networks
ssg-research/dawn-dynamic-adversarial-watermarking-of-neural-networks
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Existing watermarking schemes are ineffective against IP theft via model extraction since it is the adversary who trains the surrogate model.
Thieves on Sesame Street! Model Extraction of BERT-based APIs
google-research/language
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ICLR 2020
We study the problem of model extraction in natural language processing, in which an adversary with only query access to a victim model attempts to reconstruct a local copy of that model.
ACTIVETHIEF: Model Extraction Using Active Learning and Unannotated Public Data
We demonstrate that (1) it is possible to use ACTIVETHIEF to extract deep classifiers trained on a variety of datasets from image and text domains, while querying the model with as few as 10-30% of samples from public datasets, (2) the resulting model exhibits a higher transferability success rate of adversarial examples than prior work, and (3) the attack evades detection by the state-of-the-art model extraction detection method, PRADA.
Entangled Watermarks as a Defense against Model Extraction
cleverhans-lab/entangled-watermark
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Such pairs are watermarks, which are not sampled from the task distribution and are only known to the defender.
Cryptanalytic Extraction of Neural Network Models
google-research/cryptanalytic-model-extraction
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We argue that the machine learning problem of model extraction is actually a cryptanalytic problem in disguise, and should be studied as such.
MARLeME: A Multi-Agent Reinforcement Learning Model Extraction Library
Multi-Agent Reinforcement Learning (MARL) encompasses a powerful class of methodologies that have been applied in a wide range of fields.
Model extraction from counterfactual explanations
aivodji/mrce
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Post-hoc explanation techniques refer to a posteriori methods that can be used to explain how black-box machine learning models produce their outcomes.
MEME: Generating RNN Model Explanations via Model Extraction
dmitrykazhdan/MEME-RNN-XAI
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NeurIPS Workshop HAMLETS 2020
Recurrent Neural Networks (RNNs) have achieved remarkable performance on a range of tasks.
