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Reconstruction Attack

Facial reconstruction attack of facial manipulation models such as: Face swapping models, anonymization models, etc.

Papers

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Showing 1–50 of 68 papers

TitleStatusHype
Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and ReconstructionCode2
Trained Random Forests Completely Reveal your DatasetCode1
Reconstruct Your Previous Conversations! Comprehensively Investigating Privacy Leakage Risks in Conversations with GPT ModelsCode1
On Strengthening and Defending Graph Reconstruction Attack with Markov Chain ApproximationCode1
Confidence-Ranked Reconstruction of Census Microdata from Published StatisticsCode1
TabLeak: Tabular Data Leakage in Federated LearningCode1
Reconstructing Training Data with Informed AdversariesCode1
Inference Attacks Against Graph Neural NetworksCode1
DRAGD: A Federated Unlearning Data Reconstruction Attack Based on Gradient Differences—0
Byzantine Outside, Curious Inside: Reconstructing Data Through Malicious Updates—0
TimberStrike: Dataset Reconstruction Attack Revealing Privacy Leakage in Federated Tree-Based SystemsCode0
ReconXF: Graph Reconstruction Attack via Public Feature Explanations on Privatized Node Features and Labels—0
Cutting Through Privacy: A Hyperplane-Based Data Reconstruction Attack in Federated Learning—0
VVRec: Reconstruction Attacks on DL-based Volumetric Video Upstreaming via Latent Diffusion Model with Gamma Distribution—0
Local Differential Privacy is Not Enough: A Sample Reconstruction Attack against Federated Learning with Local Differential Privacy—0
LATTEO: A Framework to Support Learning Asynchronously Tempered with Trusted Execution and Obfuscation—0
Training Set Reconstruction from Differentially Private Forests: How Effective is DP?Code0
A Multiparty Homomorphic Encryption Approach to Confidential Federated Kaplan Meier Survival Analysis—0
Hidden Data Privacy Breaches in Federated Learning—0
Face Reconstruction from Face Embeddings using Adapter to a Face Foundation Model—0
Investigating Privacy Leakage in Dimensionality Reduction Methods via Reconstruction AttackCode0
Supervised and Unsupervised Alignments for Spoofing Behavioral Biometrics—0
Unveiling Hidden Visual Information: A Reconstruction Attack Against Adversarial Visual Information Hiding—0
Face Reconstruction Transfer Attack as Out-of-Distribution GeneralizationCode0
Bayes' capacity as a measure for reconstruction attacks in federated learning—0
UIFV: Data Reconstruction Attack in Vertical Federated Learning—0
Is Diffusion Model Safe? Severe Data Leakage via Gradient-Guided Diffusion Model—0
URVFL: Undetectable Data Reconstruction Attack on Vertical Federated LearningCode0
Visual Privacy Auditing with Diffusion Models—0
MIP: CLIP-based Image Reconstruction from PEFT Gradients—0
Bounding Reconstruction Attack Success of Adversaries Without Data Priors—0
Privacy Attacks in Decentralized LearningCode0
Data Reconstruction Attacks and Defenses: A Systematic Evaluation—0
The Inadequacy of Similarity-based Privacy Metrics: Privacy Attacks against "Truly Anonymous" Synthetic Datasets—0
Input Reconstruction Attack against Vertical Federated Large Language Models—0
An Examination of the Alleged Privacy Threats of Confidence-Ranked Reconstruction of Census MicrodataCode0
RAIFLE: Reconstruction Attacks on Interaction-based Federated Learning with Adversarial Data ManipulationCode0
FIVA: Facial Image and Video Anonymization and Anonymization Defense—0
Privacy-Preserving Medical Image Classification through Deep Learning and Matrix Decomposition—0
Approximate and Weighted Data Reconstruction Attack in Federated Learning—0
Deconstructing Classifiers: Towards A Data Reconstruction Attack Against Text Classification Models—0
Does Black-box Attribute Inference Attacks on Graph Neural Networks Constitute Privacy Risk?—0
RecUP-FL: Reconciling Utility and Privacy in Federated Learning via User-configurable Privacy Defense—0
LOKI: Large-scale Data Reconstruction Attack against Federated Learning through Model ManipulationCode0
Bounding Training Data Reconstruction in DP-SGD—0
Measuring the Privacy Leakage via Graph Reconstruction Attacks on Simplicial Neural Networks (Student Abstract)—0
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset DistillationCode0
Vicious Classifiers: Assessing Inference-time Data Reconstruction Risk in Edge ComputingCode0
HashVFL: Defending Against Data Reconstruction Attacks in Vertical Federated Learning—0
Local Model Reconstruction Attacks in Federated Learning and their Uses—0
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