Latest Articles for Data Privacy

A detailed study on how models memorize text and its implications.

Exploring Quantum Local Differential Privacy to safeguard quantum data.

New techniques improve facial image generation for recognizing genetic conditions.

New methods enhance privacy and communication in federated learning.

Examining the privacy threats posed by ECG data in healthcare.

This study examines privacy differences between decentralized and centralized federated learning.

Examining differential privacy in natural language processing for better data protection.

This article examines how defacing affects MRI image quality assessments.

Examining privacy threats linked to social connections in digital spaces.

A framework enhances security in connected vehicles while protecting user privacy.

Innovative methods enhance website identification through network traffic analysis.

Defogger offers new strategies for exploring sensitive data while ensuring privacy.

This article discusses federated learning methods and their impact on privacy and model utility.

Examining collaborative CP-NIZKs for enhanced privacy and efficiency in proofs.

This study examines the effectiveness of clean-label physical backdoor attacks in deep neural networks.

Examining the FairJob dataset to ensure equal job opportunities for all.

A new method for secure key generation among devices in wireless networks.

New framework allows for efficient removal of sensitive data from Graph Neural Networks.

Exploring machine unlearning and its role in enhancing generative AI safety and privacy.

A new method ensures secure name matching while protecting sensitive data.

OpenUAS provides a detailed view of urban area usage across Japan's major cities.

LocPIR enhances privacy in location-based services through advanced encryption.

This framework enhances AI model access and efficiency using hybrid sharding.

A fresh approach highlights surprising tokens to assess language model training data.

This article discusses a method for introducing backdoors into neural networks during training.

New methods detect and respond to memorization in AI-generated content.

Exploring principles for ethical relationships between people and their data.

A new method addresses privacy challenges in estimating U-statistics accurately.

A new method for privacy-preserving density estimation using stable list decoding.

A new method improves learning efficiency while preserving knowledge in federated learning systems.

Zero-knowledge proofs enhance privacy and security in modern digital transactions.

New methods tackle issues of copying in image generation models.

This article discusses methods to hide authorship while ensuring text usability.

AAG improves privacy and accuracy in spatial data handling.

DP-BloGS improves data privacy in machine learning while maintaining performance.

Examining the impact and risks of large language models on society.

This paper examines the effectiveness of current machine unlearning verification methods.

A new method enhances fraud detection while ensuring data privacy.

A new algorithm improves privacy and efficiency in federated learning using second-order methods.

FL-E2WS optimizes federated learning in wireless networks while ensuring data privacy.