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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 51–68 of 68 papers

TitleStatusHype
Bayes' capacity as a measure for reconstruction attacks in federated learning—0
Bounding Reconstruction Attack Success of Adversaries Without Data Priors—0
Bounding Training Data Reconstruction in DP-SGD—0
Byzantine Outside, Curious Inside: Reconstructing Data Through Malicious Updates—0
Cloud-based Federated Boosting for Mobile Crowdsensing—0
Cutting Through Privacy: A Hyperplane-Based Data Reconstruction Attack in Federated Learning—0
Data Reconstruction Attacks and Defenses: A Systematic Evaluation—0
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset Distillation—0
Deconstructing Classifiers: Towards A Data Reconstruction Attack Against Text Classification Models—0
Defending against Reconstruction Attack in Vertical Federated Learning—0
Differentially Private Instance Encoding against Privacy Attacks—0
Does Black-box Attribute Inference Attacks on Graph Neural Networks Constitute Privacy Risk?—0
DRAGD: A Federated Unlearning Data Reconstruction Attack Based on Gradient Differences—0
Face Reconstruction from Face Embeddings using Adapter to a Face Foundation Model—0
FIVA: Facial Image and Video Anonymization and Anonymization Defense—0
Fuzzy Commitments Offer Insufficient Protection to Biometric Templates Produced by Deep Learning—0
Gradient Obfuscation Gives a False Sense of Security in Federated Learning—0
Hidden Data Privacy Breaches in Federated Learning—0
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