Latest Articles for Data Privacy

Enhancing ASV systems to recognize children's voices accurately.

Examining how machine unlearning can expose sensitive data.

A novel approach to protect image privacy in technology while maintaining model performance.

Examining federated learning protocols to enhance privacy while improving model accuracy.

A look at the competition on synthetic datasets for face recognition technology.

A method to protect privacy while sharing data insights across groups.

This paper discusses how to personalize LLMs using retrieval methods for better user interactions.

A new approach to medical image analysis using federated learning and weak supervision.

A new tool for making images safer and more responsible.

Improving user experience through tailored responses in chatbots.

This project focuses on summarizing Privacy Policies using machine learning for better user comprehension.

AFedPG enhances efficiency in federated reinforcement learning through asynchronous updates.

Banks face challenges sharing trading data while protecting client privacy.

New algorithms improve privacy and optimization in machine learning models.

New methods enhance patient privacy while improving medical image research.

Analyzing threats and defenses in federated learning against malicious attacks.

Exploring privacy risks and solutions in large language models.

Exploring the vulnerabilities of ML models and potential defenses against MIAs.

EncDB offers improved security and efficiency for managing encrypted data in the cloud.

A look at improving IoT security using existing sensor data for authentication.

Researchers aim to generate balanced synthetic data to prevent bias in machine learning.

A new approach to enhance e-health through improved data management and patient privacy.

A new algorithm enhances federated learning by addressing client diversity and efficiency.

New regulations hinder medical research progress and collaboration in Finland.

An overview of legal challenges in generative AI development and use.

A method to protect data privacy in decentralized learning systems using virtual nodes.

A look at how algorithms can respect data deletion requests while maintaining efficiency.

A new tool aims to make legal agreements easier to read.

A study on improving communication in federated learning for better model performance.

A new approach to sharing trajectory data while maintaining user privacy.

This article examines how preprocessing steps can impact data privacy guarantees.

S3PHER empowers patients by enabling secure health data sharing with providers.

A look at using language models to evaluate software requirements satisfaction.

A new defense mechanism reduces label inference attack risks in collaborative machine learning.

This study enhances federated learning by boosting model diversity while protecting privacy.

A new approach for agent-based modeling safeguards individual privacy while maintaining data accuracy.

The DPV offers a clear framework for personal data handling.

A framework to enhance collaboration in healthcare while ensuring patient privacy.

Strategies for analyzing sensitive data while maintaining privacy.

Ensuring technology design respects user diversity and context.