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 101–150 of 176 papers

TitleStatusHype
Stealing Deep Reinforcement Learning Models for Fun and Profit—0
Thief, Beware of What Get You There: Towards Understanding Model Extraction Attack—0
Three-dimensional planar model estimation using multi-constraint knowledge based on k-means and RANSAC—0
Towards dialogue based, computer aided software requirements elicitation—0
Towards Few-Call Model Stealing via Active Self-Paced Knowledge Distillation and Diffusion-Based Image Generation—0
Towards Security Threats of Deep Learning Systems: A Survey—0
Unraveling Attacks in Machine Learning-based IoT Ecosystems: A Survey and the Open Libraries Behind Them—0
Using Python for Model Inference in Deep Learning—0
Was my Model Stolen? Feature Sharing for Robust and Transferable Watermarks—0
Watermarking Graph Neural Networks based on Backdoor Attacks—0
Few-shot Model Extraction Attacks against Sequential Recommender Systems—0
Fingerprinting Deep Neural Networks Globally via Universal Adversarial Perturbations—0
First to Possess His Statistics: Data-Free Model Extraction Attack on Tabular Data—0
"FRAME: Forward Recursive Adaptive Model Extraction -- A Technique for Advance Feature Selection"—0
Fraternal Twins: Unifying Attacks on Machine Learning and Digital Watermarking—0
GENIE: Watermarking Graph Neural Networks for Link Prediction—0
Good Artists Copy, Great Artists Steal: Model Extraction Attacks Against Image Translation Models—0
Grey-box Extraction of Natural Language Models—0
GrOVe: Ownership Verification of Graph Neural Networks using Embeddings—0
HODA: Hardness-Oriented Detection of Model Extraction Attacks—0
High Accuracy and High Fidelity Extraction of Neural Networks—0
HODA: Protecting DNNs Against Model Extraction Attacks via Hardness of Samples—0
HoneypotNet: Backdoor Attacks Against Model Extraction—0
Increasing the Cost of Model Extraction with Calibrated Proof of Work—0
Interpretability via Model Extraction—0
Interpreting Blackbox Models via Model Extraction—0
Killing One Bird with Two Stones: Model Extraction and Attribute Inference Attacks against BERT-based APIs—0
Noisy Data Meets Privacy: Training Local Models with Post-Processed Remote Queries—0
Learnable Linguistic Watermarks for Tracing Model Extraction Attacks on Large Language Models—0
Leveraging Extracted Model Adversaries for Improved Black Box Attacks—0
Like an Open Book? Read Neural Network Architecture with Simple Power Analysis on 32-bit Microcontrollers—0
MaskedNet: The First Hardware Inference Engine Aiming Power Side-Channel Protection—0
MEAOD: Model Extraction Attack against Object Detectors—0
MEGEX: Data-Free Model Extraction Attack against Gradient-Based Explainable AI—0
Mercury: An Automated Remote Side-channel Attack to Nvidia Deep Learning Accelerator—0
Mitigating Query-Flooding Parameter Duplication Attack on Regression Models with High-Dimensional Gaussian Mechanism—0
Model Extraction and Adversarial Attacks on Neural Networks using Switching Power Information—0
Robust and Minimally Invasive Watermarking for EaaSCode0
WARDEN: Multi-Directional Backdoor Watermarks for Embedding-as-a-Service Copyright ProtectionCode0
Process Extraction from Text: Benchmarking the State of the Art and Paving the Way for Future ChallengesCode0
Weighted Automata Extraction and Explanation of Recurrent Neural Networks for Natural Language TasksCode0
FLuID: Mitigating Stragglers in Federated Learning using Invariant DropoutCode0
Stateful Detection of Model Extraction AttacksCode0
Protecting Intellectual Property of Language Generation APIs with Lexical WatermarkCode0
From Counterfactuals to Trees: Competitive Analysis of Model Extraction AttacksCode0
Model Extraction Attacks on Graph Neural Networks: Taxonomy and RealizationCode0
ACTIVETHIEF: Model Extraction Using Active Learning and Unannotated Public DataCode0
Watermarking Counterfactual ExplanationsCode0
Model extraction from counterfactual explanationsCode0
GUIDO: A Hybrid Approach to Guideline Discovery & Ordering from Natural Language TextsCode0
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Benchmark Results

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