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 131–140 of 176 papers

TitleStatusHype
A Novel Watermarking Framework for Ownership Verification of DNN Architectures—0
A Practical Introduction to Side-Channel Extraction of Deep Neural Network Parameters—0
A Review of Confidentiality Threats Against Embedded Neural Network Models—0
A Survey of Model Extraction Attacks and Defenses in Distributed Computing Environments—0
A Survey on Event-based News Narrative Extraction—0
AUTOLYCUS: Exploiting Explainable AI (XAI) for Model Extraction Attacks against Interpretable Models—0
Automated Data-Driven Model Extraction and Validation of Inverter Dynamics with Grid Support Function—0
Automating Agential Reasoning: Proof-Calculi and Syntactic Decidability for STIT Logics—0
Better Decisions through the Right Causal World Model—0
Beyond Labeling Oracles: What does it mean to steal ML models?—0
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Benchmark Results

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