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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
Feature Reconstruction Attacks and Countermeasures of DNN training in Vertical Federated LearningCode0
PrivMVMF: Privacy-Preserving Multi-View Matrix Factorization for Recommender Systems—0
Privacy Safe Representation Learning via Frequency Filtering Encoder—0
Differentially Private Instance Encoding against Privacy Attacks—0
Gradient Obfuscation Gives a False Sense of Security in Federated Learning—0
How Private Is Your RL Policy? An Inverse RL Based Analysis FrameworkCode0
When the Curious Abandon Honesty: Federated Learning Is Not PrivateCode0
Reconstruction Attack on Instance Encoding for Language Understanding—0
Towards General Deep Leakage in Federated LearningCode0
A Novel Attribute Reconstruction Attack in Federated Learning—0
Defending against Reconstruction Attack in Vertical Federated Learning—0
A Review of Anonymization for Healthcare DataCode0
Fuzzy Commitments Offer Insufficient Protection to Biometric Templates Produced by Deep Learning—0
Exploring the Security Boundary of Data Reconstruction via Neuron Exclusivity Analysis—0
SAPAG: A Self-Adaptive Privacy Attack From Gradients—0
Vulnerability of Face Recognition Systems Against Composite Face Reconstruction Attack—0
Cloud-based Federated Boosting for Mobile Crowdsensing—0
On the Reconstruction of Face Images from Deep Face Templates—0
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