Latest Articles for Data Privacy

A node-private algorithm for analyzing graph components protects individual privacy.

Exploring federated learning in decision-making with contextual bandits and privacy preservation.

Exploring ABS's approach to safeguard privacy while delivering essential statistical information.

Vers enhances distributed computing through decentralized data handling and robust security.

CIM systems improve efficiency but expose vulnerabilities to side-channel attacks.

MedAlpaca enhances medical AI models and training data for better patient care.

PFELS combines privacy and energy efficiency in federated learning.

New method enhances driver behavior monitoring while protecting privacy.

Examining local differential privacy and its vulnerabilities in protecting user data.

TimelyFL enhances federated learning by optimizing device contributions and improving model accuracy.

FedLSM enhances collaboration in medical imaging by addressing label mismatches.

FedXGBllr enhances federated learning by improving privacy and communication efficiency.

New system aims to protect patient anonymity in hospital data for AI research.

Balancing data sharing benefits with personal privacy protection methods.

A new approach ensures data privacy while maintaining model performance.

Explore new tools for decentralized learning in machine learning.

A new method protects privacy while ensuring accurate consensus among agents in networks.

DRIFT enhances recommender systems while ensuring user privacy through local data processing.

A look at methods to increase device participation in federated learning.

Examining Differentially Private Stochastic Convex Optimization across diverse settings.

A new model improves privacy and accuracy in graph neural networks.

A close look at Booking.com's use of customer data and privacy policies.

Examining privacy attacks in Split Learning and a new protective method.

Learn about Quantum Key Distribution and its role in secure data sharing.

DPAF offers high-quality synthetic images while ensuring strong privacy protections.

This article discusses methods to remove backdoors from federated learning models.

Strategies to protect user privacy while optimizing communication in data analytics.

Exploring the balance between open data access and personal privacy risks.

Research aims to forecast memorization behavior in language models for better privacy control.

Learn about the dangers of model poisoning attacks and their impact on federated learning.

This research presents a method to enhance communication in federated learning.

A new method for creating synthetic GPS data while ensuring user privacy.

A new method improves model training while protecting patient privacy.

Federated Learning offers a way to improve healthcare data use while protecting patient privacy.

Analyzing dataset use in voice biometrics reveals significant bias and privacy concerns.

Exploring methods for organizations to share sensitive data while protecting privacy.

Enhancing model performance while protecting user privacy in federated learning.

A study on how LDP affects fairness in machine learning.

Learn how WFL improves data use without compromising privacy.

Exploring privacy risks in self-supervised learning due to unintended memorization.