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Reconstruction Attack
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Facial reconstruction attack of facial manipulation models such as: Face swapping models, anonymization models, etc.
논문
이 태스크와 하위 분야의 관련 논문입니다. 실제 성능 비교는 평가 결과에서 확인하세요.
Byzantine Outside, Curious Inside: Reconstructing Data Through Malicious Updates
TimberStrike: Dataset Reconstruction Attack Revealing Privacy Leakage in Federated Tree-Based Systems
ReconXF: Graph Reconstruction Attack via Public Feature Explanations on Privatized Node Features and Labels
Cutting Through Privacy: A Hyperplane-Based Data Reconstruction Attack in Federated Learning
VVRec: Reconstruction Attacks on DL-based Volumetric Video Upstreaming via Latent Diffusion Model with Gamma Distribution
Local Differential Privacy is Not Enough: A Sample Reconstruction Attack against Federated Learning with Local Differential Privacy
LATTEO: A Framework to Support Learning Asynchronously Tempered with Trusted Execution and Obfuscation
Training Set Reconstruction from Differentially Private Forests: How Effective is DP?
A Multiparty Homomorphic Encryption Approach to Confidential Federated Kaplan Meier Survival Analysis
Hidden Data Privacy Breaches in Federated Learning
Face Reconstruction from Face Embeddings using Adapter to a Face Foundation Model
Investigating Privacy Leakage in Dimensionality Reduction Methods via Reconstruction Attack
Supervised and Unsupervised Alignments for Spoofing Behavioral Biometrics
Unveiling Hidden Visual Information: A Reconstruction Attack Against Adversarial Visual Information Hiding
Face Reconstruction Transfer Attack as Out-of-Distribution Generalization
Bayes' capacity as a measure for reconstruction attacks in federated learning
UIFV: Data Reconstruction Attack in Vertical Federated Learning
Is Diffusion Model Safe? Severe Data Leakage via Gradient-Guided Diffusion Model
URVFL: Undetectable Data Reconstruction Attack on Vertical Federated Learning
Visual Privacy Auditing with Diffusion Models
Trained Random Forests Completely Reveal your Dataset
Making Them Ask and Answer: Jailbreaking Large Language Models in Few Queries via Disguise and Reconstruction
MIP: CLIP-based Image Reconstruction from PEFT Gradients
Bounding Reconstruction Attack Success of Adversaries Without Data Priors
Privacy Attacks in Decentralized Learning
Data Reconstruction Attacks and Defenses: A Systematic Evaluation
Reconstruct Your Previous Conversations! Comprehensively Investigating Privacy Leakage Risks in Conversations with GPT Models
The Inadequacy of Similarity-based Privacy Metrics: Privacy Attacks against "Truly Anonymous" Synthetic Datasets
Input Reconstruction Attack against Vertical Federated Large Language Models
An Examination of the Alleged Privacy Threats of Confidence-Ranked Reconstruction of Census Microdata
RAIFLE: Reconstruction Attacks on Interaction-based Federated Learning with Adversarial Data Manipulation
FIVA: Facial Image and Video Anonymization and Anonymization Defense
Privacy-Preserving Medical Image Classification through Deep Learning and Matrix Decomposition
Approximate and Weighted Data Reconstruction Attack in Federated Learning
Deconstructing Classifiers: Towards A Data Reconstruction Attack Against Text Classification Models
출처: Papers with Code · CC BY-SA 4.0. 아카이브 자료와 새로 수집한 논문은 별도로 관리합니다.