SOTAVerified

Privacy Preserving

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Showing 1951–2000 of 2975 papers

TitleStatusHype
Secure multiparty computations in floating-point arithmetic—0
SFPDML: Securer and Faster Privacy-Preserving Distributed Machine Learning based on MKTFHE—0
Secure Social Recommendation based on Secret Sharing—0
Secure Split Learning against Property Inference, Data Reconstruction, and Feature Space Hijacking Attacks—0
Secure Sum Outperforms Homomorphic Encryption in (Current) Collaborative Deep Learning—0
Secure Visual Data Processing via Federated Learning—0
Securing Federated Learning against Overwhelming Collusive Attackers—0
Securing Genomic Data Against Inference Attacks in Federated Learning Environments—0
Securing the Classification of COVID-19 in Chest X-ray Images: A Privacy-Preserving Deep Learning Approach—0
Securing the Future: Innovations in Privacy-Preserving Integrated Sensing for Industrial Cyber-Physical Systems—0
Security and Privacy Preserving Deep Learning—0
Security of Internet of Agents: Attacks and Countermeasures—0
Security Protection in Cooperative Control of Multi-agent Systems—0
Contrasting Adversarial Perturbations: The Space of Harmless Perturbations—0
See through Gradients: Image Batch Recovery via GradInversion—0
SegLoc: Learning Segmentation-Based Representations for Privacy-Preserving Visual Localization—0
Selective, Interpretable, and Motion Consistent Privacy Attribute Obfuscation for Action Recognition—0
Selective Interpretable and Motion Consistent Privacy Attribute Obfuscation for Action Recognition—0
Self-supervised Normality Learning and Divergence Vector-guided Model Merging for Zero-shot Congenital Heart Disease Detection in Fetal Ultrasound Videos—0
Semi-Decentralized Federated Edge Learning with Data and Device Heterogeneity—0
Semi-decentralized Federated Ego Graph Learning for Recommendation—0
Sensing-Resistance-Oriented Beamforming for Privacy Protection from ISAC Devices—0
Training Large Scale Polynomial CNNs for E2E Inference over Homomorphic Encryption—0
SF-PATE: Scalable, Fair, and Private Aggregation of Teacher Ensembles—0
SFPrompt: Communication-Efficient Split Federated Fine-Tuning for Large Pre-Trained Models over Resource-Limited Devices—0
SHADE-AD: An LLM-Based Framework for Synthesizing Activity Data of Alzheimer's Patients—0
Shared MF: A privacy-preserving recommendation system—0
Share your Model instead of your Data: Privacy Preserving Mimic Learning for Ranking—0
Sharing FANCI Features: A Privacy Analysis of Feature Extraction for DGA Detection—0
Sharing is CAIRing: Characterizing Principles and Assessing Properties of Universal Privacy Evaluation for Synthetic Tabular Data—0
Shielding the Unseen: Privacy Protection through Poisoning NeRF with Spatial Deformation—0
Shuffled Differentially Private Federated Learning for Time Series Data Analytics—0
Simple Yet Effective: Extracting Private Data Across Clients in Federated Fine-Tuning of Large Language Models—0
Simplified Swarm Learning Framework for Robust and Scalable Diagnostic Services in Cancer Histopathology—0
Smart-Badge: A wearable badge with multi-modal sensors for kitchen activity recognition—0
Smart Policy Control for Securing Federated Learning Management System—0
SMOTE-DP: Improving Privacy-Utility Tradeoff with Synthetic Data—0
Sniper GMMs: Structured Gaussian mixtures poison ML on large n small p data with high efficacy—0
SocialGuard: An Adversarial Example Based Privacy-Preserving Technique for Social Images—0
Social Vehicle Swarms: A Novel Perspective on Social-aware Vehicular Communication Architecture—0
Sociodynamics-inspired Adaptive Coalition and Client Selection in Federated Learning—0
Soft-Hard Attention U-Net Model and Benchmark Dataset for Multiscale Image Shadow Removal—0
SoK: Can Synthetic Images Replace Real Data? A Survey of Utility and Privacy of Synthetic Image Generation—0
SoK: Modeling Explainability in Security Analytics for Interpretability, Trustworthiness, and Usability—0
On the Impossible Safety of Large AI Models—0
SoK: Privacy-Preserving Collaborative Tree-based Model Learning—0
SoK: Privacy-Preserving Data Synthesis—0
SoK: Privacy-preserving Deep Learning with Homomorphic Encryption—0
SoK: Privacy Preserving Machine Learning using Functional Encryption: Opportunities and Challenges—0
SoK: Training Machine Learning Models over Multiple Sources with Privacy Preservation—0
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