Latest Articles for Data Privacy

A closer look at disclosure risks in synthetic data and privacy protection.

Sri Lanka enacts privacy law to protect patient data in health apps.

FedDM enhances federated learning for diffusion models while ensuring data privacy.

Exploring differential privacy to protect sensitive information in AI applications.

A new approach aims to protect user privacy while improving result accuracy.

Federated learning enhances machine learning while ensuring data privacy in industrial settings.

A new method improves dataset distillation, enhancing model training efficiency.

A new method improves medical imaging while securing patient data.

Examining the role of robustness in estimating unknown distributions from samples.

A study on improving software through user reviews and ethical insights.

A new method enhances security for smart grids while maintaining user privacy.

Exploring risks and defense strategies for large language models.

CCNet enhances model performance on new data while preserving user privacy.

PUFFLE offers a solution for privacy, utility, and fairness challenges in machine learning.

A framework enabling data owners to check unauthorized use of their data in ML.

A study introduces SeqMIA to improve privacy against membership inference attacks.

A new approach to improve medical image classification while preserving patient privacy.

New architecture enhances video analysis on small devices using multiple frames.

A study on improving wireless communication through advanced tracking and prediction methods.

This study reveals new methods for reconstructing training data from high-resolution images.

This article evaluates web agents' effectiveness in managing complex online tasks.

A new system enhances security for vehicles in the 6G era.

Examining the advantages and dangers of AI in our daily mobile technology.

This article explores Knowledge Recycling for improving synthetic data training in classifiers.

This method enhances privacy while improving model accuracy in AI.

Introducing a framework that balances privacy and effective social event detection.

A novel approach to enhance performance in hierarchical federated learning.

A new programming language improves MPC protocol security verification.

Federated learning offers a way to utilize data while maintaining user privacy.

This paper discusses the Poisson mechanism for maintaining privacy in data synthesis.

A new method improves secure data analysis while protecting privacy.

Exploring techniques for effectively removing data from AI models.

Exploring the role of spiking neural networks in vertical federated learning for data privacy.

A web-based tool making image analysis accessible for scientists without programming skills.

Exploring the use of watermarks to tackle copyright issues in language models.

This article explores security challenges and testing methods for 5G networks.

A new system enhances ML inference speed while preserving data privacy.

A new synthetic dataset enables accurate head detection and 3D modeling.

A look at the shuffle model's approach to protecting user data privacy.

New method enhances synthetic data generation while ensuring privacy protection.