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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
Measuring the Privacy Leakage via Graph Reconstruction Attacks on Simplicial Neural Networks (Student Abstract)—0
MIP: CLIP-based Image Reconstruction from PEFT Gradients—0
How Private Is Your RL Policy? An Inverse RL Based Analysis FrameworkCode0
Feature Reconstruction Attacks and Countermeasures of DNN training in Vertical Federated LearningCode0
LOKI: Large-scale Data Reconstruction Attack against Federated Learning through Model ManipulationCode0
Investigating Privacy Leakage in Dimensionality Reduction Methods via Reconstruction AttackCode0
Vicious Classifiers: Assessing Inference-time Data Reconstruction Risk in Edge ComputingCode0
When the Curious Abandon Honesty: Federated Learning Is Not PrivateCode0
URVFL: Undetectable Data Reconstruction Attack on Vertical Federated LearningCode0
RAIFLE: Reconstruction Attacks on Interaction-based Federated Learning with Adversarial Data ManipulationCode0
A Review of Anonymization for Healthcare DataCode0
Face Reconstruction Transfer Attack as Out-of-Distribution GeneralizationCode0
TimberStrike: Dataset Reconstruction Attack Revealing Privacy Leakage in Federated Tree-Based SystemsCode0
Towards General Deep Leakage in Federated LearningCode0
Understanding Reconstruction Attacks with the Neural Tangent Kernel and Dataset DistillationCode0
An Examination of the Alleged Privacy Threats of Confidence-Ranked Reconstruction of Census MicrodataCode0
Training Set Reconstruction from Differentially Private Forests: How Effective is DP?Code0
Privacy Attacks in Decentralized LearningCode0
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