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 51–75 of 176 papers

TitleStatusHype
Knowledge Distillation-Based Model Extraction Attack using GAN-based Private Counterfactual ExplanationsCode0
From Counterfactuals to Trees: Competitive Analysis of Model Extraction AttacksCode0
Marich: A Query-efficient Distributionally Equivalent Model Extraction Attack using Public DataCode0
Model Reconstruction Using Counterfactual Explanations: A Perspective From Polytope TheoryCode0
Model Extraction Attacks on Graph Neural Networks: Taxonomy and RealizationCode0
Protecting Intellectual Property of Language Generation APIs with Lexical WatermarkCode0
Towards Automatically Extracting UML Class Diagrams from Natural Language SpecificationsCode0
Evaluating Query Efficiency and Accuracy of Transfer Learning-based Model Extraction Attack in Federated Learning—0
Entangled Threats: A Unified Kill Chain Model for Quantum Machine Learning Security—0
Student Surpasses Teacher: Imitation Attack for Black-Box NLP APIs—0
An anatomy-based V1 model: Extraction of Low-level Features, Reduction of distortion and a V1-inspired SOM—0
Enhancing TinyML Security: Study of Adversarial Attack Transferability—0
Emerging AI Security Threats for Autonomous Cars -- Case Studies—0
Beyond Labeling Oracles: What does it mean to steal ML models?—0
Efficient Model Extraction via Boundary Sampling—0
Efficiently Learning One Hidden Layer ReLU Networks From Queries—0
Better Decisions through the Right Causal World Model—0
Adversarial Exploitation of Policy Imitation—0
Efficiently Learning Any One Hidden Layer ReLU Network From Queries—0
Automating Agential Reasoning: Proof-Calculi and Syntactic Decidability for STIT Logics—0
DynaMarks: Defending Against Deep Learning Model Extraction Using Dynamic Watermarking—0
DualCF: Efficient Model Extraction Attack from Counterfactual Explanations—0
Automated Data-Driven Model Extraction and Validation of Inverter Dynamics with Grid Support Function—0
Don't encrypt the data; just approximate the model \ Towards Secure Transaction and Fair Pricing of Training Data—0
Differentially private fine-tuned NF-Net to predict GI cancer type—0
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Benchmark Results

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