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 31–40 of 176 papers

TitleStatusHype
Differentially private fine-tuned NF-Net to predict GI cancer type—0
From Counterfactuals to Trees: Competitive Analysis of Model Extraction AttacksCode0
A Framework for Double-Blind Federated Adaptation of Foundation Models—0
Data-Free Model-Related Attacks: Unleashing the Potential of Generative AI—0
"FRAME: Forward Recursive Adaptive Model Extraction -- A Technique for Advance Feature Selection"—0
HoneypotNet: Backdoor Attacks Against Model Extraction—0
Bounding-box Watermarking: Defense against Model Extraction Attacks on Object Detectors—0
Few-shot Model Extraction Attacks against Sequential Recommender Systems—0
A Hard-Label Cryptanalytic Extraction of Non-Fully Connected Deep Neural Networks using Side-Channel AttacksCode0
Your Semantic-Independent Watermark is Fragile: A Semantic Perturbation Attack against EaaS WatermarkCode0
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Benchmark Results

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