SOTAVerified

Model extraction

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 and replicate a model that will have a very similar performance to the target model.

Papers

Showing 126150 of 176 papers

TitleStatusHype
Model Extraction and Adversarial Attacks on Neural Networks using Switching Power Information0
Killing One Bird with Two Stones: Model Extraction and Attribute Inference Attacks against BERT-based APIs0
An Exact Poly-Time Membership-Queries Algorithm for Extraction a three-Layer ReLU Network0
A Review of Confidentiality Threats Against Embedded Neural Network Models0
Good Artists Copy, Great Artists Steal: Model Extraction Attacks Against Image Translation Models0
Thief, Beware of What Get You There: Towards Understanding Model Extraction Attack0
Using Python for Model Inference in Deep Learning0
Model Extraction and Adversarial Transferability, Your BERT is Vulnerable!Code1
BODAME: Bilevel Optimization for Defense Against Model Extraction0
Model Extraction and Defenses on Generative Adversarial Networks0
EXPLORING VULNERABILITIES OF BERT-BASED APIS0
Grey-box Extraction of Natural Language Models0
MEME: Generating RNN Model Explanations via Model ExtractionCode1
Sparsity-driven Digital Terrain Model Extraction0
Data-Free Model ExtractionCode1
A Knowledge Representation Approach to Automated Mathematical Modelling0
Monitoring-based Differential Privacy Mechanism Against Query-Flooding Parameter Duplication Attack0
Leveraging Extracted Model Adversaries for Improved Black Box Attacks0
Now You See Me (CME): Concept-based Model ExtractionCode1
Model Extraction Attacks on Graph Neural Networks: Taxonomy and RealizationCode0
MEME: Generating RNN Model Explanations via Model ExtractionCode1
Model extraction from counterfactual explanationsCode0
Stealing Deep Reinforcement Learning Models for Fun and Profit0
MARLeME: A Multi-Agent Reinforcement Learning Model Extraction LibraryCode1
Cryptanalytic Extraction of Neural Network ModelsCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1three-step-originalExact Match0.17Unverified