Latest Articles for Data Privacy

A new method addresses data challenges in AI for healthcare.

New methods for statistical testing while protecting data privacy through federated learning.

Exploring challenges and advancements in protecting sensitive data while maintaining its usefulness.

The challenge of combining differential privacy with sublinear algorithms in data analysis.

A look at federated learning combining differential privacy and blockchain for data security.

A study on federated learning systems using blockchain for secure collaboration.

Explore the fundamentals of Federated Learning and its importance in data privacy.

A new framework evaluates methods for anonymizing biometric data to enhance privacy.

Examining methods to protect privacy in deep learning applications using visual information encryption.

A new model improves data privacy while enhancing machine learning accuracy.

Exploring user-level differential privacy in large language model training.

A method to enhance model training using partially labeled medical images.

Exploring the benefits of Federated Learning for anomaly detection in IoT networks.

EFVFL provides a stable method for efficient communication without sharing private data.

A look at federated learning’s privacy and integrity challenges and solutions.

VQA models may expose private information despite advanced techniques.

Regulations guide the safe and fair use of AI technologies across various sectors.

Research highlights model robustness and defenses in decentralized federated learning.

A new method improves AI performance using public datasets while protecting patient privacy.

New methods tackle privacy risks in human movement data prediction.

This paper presents methods to enhance model performance while ensuring data privacy.

A fresh method to compare privacy mechanisms in machine learning.

A new method improves privacy while training deep learning models.

This article discusses machine unlearning and its implications for data privacy.

A novel approach to enhance security in federated learning against backdoor attacks.

A new framework aids small developers in creating RoPA using user experiences.

New methods for federated learning improve efficiency and privacy in IoT networks.

A look at synthetic data generation for urban mobility and privacy challenges.

New methods are ensuring privacy in genomic data research.

Introducing FedGTG to retain knowledge while learning in federated settings.

New methods enhance privacy protection in large language models.

A new method enhances the security of deep learning models against hidden threats.

Synthetic data generation aids healthcare research while protecting patient privacy.

New models improve tissue image quality for better disease diagnosis.

MedUniverse enhances medical imaging tools while protecting patient privacy.

This article discusses retraining methods using model predictions for improved accuracy.

Discover how synthetic data helps retailers protect customer privacy while gaining insights.

Exploring privacy risks in synthetic data and introducing the Data Plagiarism Index.

Analyzing effective clean-label backdoor attack techniques in machine learning.

Federated learning enhances medical imaging while protecting patient data.