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 71–80 of 176 papers

TitleStatusHype
Automated Data-Driven Model Extraction and Validation of Inverter Dynamics with Grid Support Function—0
GUIDO: A Hybrid Approach to Guideline Discovery & Ordering from Natural Language TextsCode0
FLuID: Mitigating Stragglers in Federated Learning using Invariant DropoutCode0
Pareto-Secure Machine Learning (PSML): Fingerprinting and Securing Inference Serving Systems—0
Weighted Automata Extraction and Explanation of Recurrent Neural Networks for Natural Language TasksCode0
FDINet: Protecting against DNN Model Extraction via Feature Distortion Index—0
Ownership Protection of Generative Adversarial Networks—0
NaturalFinger: Generating Natural Fingerprint with Generative Adversarial Networks—0
Are You Copying My Model? Protecting the Copyright of Large Language Models for EaaS via Backdoor WatermarkCode1
Model Extraction Attacks Against Reinforcement Learning Based Controllers—0
Show:102550
← PrevPage 8 of 18Next →

Benchmark Results

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