Latest Articles for Data Privacy

Federated Learning improves translation efficiency while ensuring data privacy.

Exploring Multi-Model Asynchronous Federated Learning for improved efficiency and privacy.

Assessing privacy concerns and solutions in Split Learning methods.

A novel method enhances small language models while protecting patient privacy.

Scafflix improves communication in Federated Learning while ensuring data privacy.

FedVS improves model training speed and privacy in vertical federated learning.

Enhancing data privacy in cloud storage through efficient encryption solutions.

Analyzing side-channel attacks on power-efficient devices.

New methods improve secure key generation and transmission distance.

This study reviews synthetic data generation methods for health research, focusing on privacy and quality.

Bounded metrics improve data safety while retaining utility for analysis.

A look into federated learning's impact on privacy and fairness.

This method analyzes medical images while keeping patient identities safe.

WeiAvg enhances federated learning by prioritizing data diversity while safeguarding privacy.

Examining vulnerabilities in large language models and strategies for better protection.

A look at how quantum communication outperforms classical methods in multi-party computations.

New methods protect sensitive information in prompts for language models.

A new method improves privacy in decision trees without sacrificing accuracy.

Using synthetic images to enhance ultrasound analysis and training.

A new tool helps developers create clear privacy notices for mobile applications.

Learn how Local SGD improves model training efficiency and data privacy.

Examining how chatbots handle sensitive information and privacy issues.

A new system simplifies privacy policy annotations for better public awareness.

Balancing privacy concerns with the need for effective data analysis.

This study investigates the trade-off between fairness and privacy in language models.

A new method using MPC to secure data while identifying accurate information.

Synthetic images offer new solutions for medical training and patient privacy.

This article explores the privacy implications of Gaussian Process Regression in machine learning.

FairDP offers a solution for ensuring privacy and fairness in machine learning systems.

A new framework enhancing speed and privacy in natural language generation.

A study on how diffusion models and GANs generate synthetic medical images.

A new framework enhances vertical federated learning efficiency and privacy using Cloud-RAN technology.

vFedSec offers secure, efficient training for machine learning models in federated settings.

A look at new encoding methods for better data privacy.

Assessing privacy risks in deep learning against various attacks.

Reforming public health to improve response to future health crises.

A new protocol to protect user privacy in 5G network slicing.

PPA-AFL improves data privacy in collaborative machine learning across devices.

Exploring federated learning and the interior point method for effective model training.

A framework to develop personalized policies using observational data while ensuring privacy.