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

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Showing 21–30 of 176 papers

TitleStatusHype
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
Robust and Minimally Invasive Watermarking for EaaSCode0
Efficient Model Extraction via Boundary Sampling—0
Efficient and Effective Model ExtractionCode0
CaBaGe: Data-Free Model Extraction using ClAss BAlanced Generator Ensemble—0
Protecting Copyright of Medical Pre-trained Language Models: Training-Free Backdoor Model Watermarking—0
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Benchmark Results

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