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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–176 of 176 papers

TitleStatusHype
Stealing Machine Learning Models via Prediction APIsCode0
Model Reconstruction Using Counterfactual Explanations: A Perspective From Polytope TheoryCode0
Stealing and Evading Malware Classifiers and Antivirus at Low False Positive ConditionsCode0
The Power of MEME: Adversarial Malware Creation with Model-Based Reinforcement LearningCode0
Safe and Robust Watermark Injection with a Single OoD ImageCode0
VidModEx: Interpretable and Efficient Black Box Model Extraction for High-Dimensional SpacesCode0
Army of Thieves: Enhancing Black-Box Model Extraction via Ensemble based sample selectionCode0
Not Just Change the Labels, Learn the Features: Watermarking Deep Neural Networks with Multi-View DataCode0
Knowledge Distillation-Based Model Extraction Attack using GAN-based Private Counterfactual ExplanationsCode0
A Hard-Label Cryptanalytic Extraction of Non-Fully Connected Deep Neural Networks using Side-Channel AttacksCode0
SAME: Sample Reconstruction against Model Extraction AttacksCode0
On the Difficulty of Defending Self-Supervised Learning against Model ExtractionCode0
On the Effectiveness of Dataset Watermarking in Adversarial SettingsCode0
Marich: A Query-efficient Distributionally Equivalent Model Extraction Attack using Public DataCode0
Efficient and Effective Model ExtractionCode0
DAWN: Dynamic Adversarial Watermarking of Neural NetworksCode0
Defense Against Model Extraction Attacks on Recommender SystemsCode0
MeaeQ: Mount Model Extraction Attacks with Efficient QueriesCode0
Your Semantic-Independent Watermark is Fragile: A Semantic Perturbation Attack against EaaS WatermarkCode0
Thieves on Sesame Street! Model Extraction of BERT-based APIsCode0
Deep Neural Network Fingerprinting by Conferrable Adversarial ExamplesCode0
CEGA: A Cost-Effective Approach for Graph-Based Model Extraction and AcquisitionCode0
An Approach for Process Model Extraction By Multi-Grained Text ClassificationCode0
MISLEADER: Defending against Model Extraction with Ensembles of Distilled ModelsCode0
Towards Automatically Extracting UML Class Diagrams from Natural Language SpecificationsCode0
Beyond Slow Signs in High-fidelity Model ExtractionCode0
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Benchmark Results

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