Latest Articles for Data Privacy

Learn how PPSR protects data privacy in symbolic regression tasks.

FedIns tackles data challenges in federated learning to improve model performance.

CyberForce combines learning strategies to protect IoT devices from malware.

Web 3.0 changes online interaction, giving users more control over their data.

A model to simplify data regulation compliance for organizations.

A new method enhances UAV participation in federated learning while protecting privacy.

A new method improves network traffic management while protecting user privacy.

This article discusses managing communication noise in federated learning for better model performance.

An innovative method for collaborative machine learning while keeping data private.

A new method allows machine learning models to forget data effectively and swiftly.

A novel approach to safeguard sensitive data captured by self-driving cars.

A new method for drawing insights from summarized data using Gibbs sampling.

Examining the impact of cookie notices on users with visual impairments.

Examining the challenges and opportunities of differential privacy in data analysis.

A method for personalized machine learning in federated learning environments.

A new approach uses speech patterns to identify depression relapse more effectively.

Examining risks in shared state of AR applications and ways to enhance security.

Synthetic data generation enhances privacy while enabling valuable data analysis.

A new framework enhances federated learning in multi-cloud settings.

MixBag enhances learning from label proportions by creating new labeled groups.

The new model shifts focus to item popularity for better recommendations.

Research explores balance in multilingual language models for fairness and privacy.

A novel approach allows training neural networks efficiently on small devices without backward propagation.

An exploration of how Saudi users perceive privacy in Google services.

Disposable Transfer Learning addresses privacy concerns while maintaining model performance.

SplitWiper improves unlearning in machine learning, ensuring data privacy and efficiency.

Federated Learning enhances connected vehicle safety while protecting user data.

Exploring a new method to protect privacy in causal research while maintaining accuracy.

Exploring split learning's benefits for secure healthcare model training.

New method improves privacy while enabling better use of healthcare data.

A new approach enhances MRI image quality while ensuring data privacy.

Examining the privacy threats posed by data collection in smart vehicles.

Addressing the need for accurate sustainability in data centers.

Using Federated Learning to improve PCOS treatment while ensuring patient privacy.

FedSoL improves local learning while maintaining global model alignment.

User-Level Differential Privacy offers a better privacy approach in data sharing.

New methods improve communication and privacy in neuroimaging research using federated learning.

A new method minimizes bias while maintaining privacy in machine learning.

A new method enhances detection accuracy in IoT networks using semi-supervised and semi-asynchronous learning.

Exploring challenges and solutions for implementing federated learning in IoT devices.