Latest Articles for Data Privacy

LightTR enhances trajectory recovery using federated learning while protecting user privacy.

Mind-Animator reconstructs videos using brain activity measured by fMRI.

Media organizations create guidelines for responsible AI use in journalism.

Using Generative AI and MoE for improved communication security.

New method improves device selection efficiency in federated learning.

A new method addresses privacy and fairness in regression models using innovative adjustments.

New method protects privacy while allowing language models to learn from examples.

A framework for safer data processing in machine learning.

Inductive GNNs face privacy threats from link stealing attacks.

A new method improving medical data privacy and collaboration between institutions.

This study explores Federated Learning's role in Document Visual Question Answering.

Shadow-free MIAs reveal vulnerabilities in user recommendation systems.

A new approach to enhance client availability in federated learning.

A new framework generates human mobility data while protecting individual privacy.

A new protocol enhances privacy and efficiency in decentralized learning.

A look into the risks of Membership Inference Attacks on data privacy.

A look into how Sparse Models improve Federated Learning efficiency.

New AI model improves diagnosis of bone issues using X-ray and report data.

Learn how differential privacy can enhance data security in LLS regression.

A system that learns from patient data while ensuring privacy protections.

AI professionals share their views on Trustworthy AI and its challenges.

A new approach combines privacy protections with contextual bandit learning.

A new method for detecting vehicle misbehavior while protecting privacy.

A study on improving video stream detection while maintaining user privacy.

A method to erase identities from generative models while maintaining image quality.

New methods improve accuracy in join size estimation while protecting sensitive data.

A strategy to protect sensitive connections in graph data while releasing useful information.

A look at differential privacy and its application in machine learning.

A new method enhances decentralized federated learning while maintaining data privacy.

A new approach enhances intrusion detection in decentralized systems.

Improving mobile sensing applications through a novel framework for managing missing data.

This study examines how creators respond when their works are used for AI training.

This paper presents EFRAP, a defense against quantization-conditioned backdoor attacks in deep learning models.

A new method enhances the ability of models to forget specific visual information.

Methods to provide reliable population estimates while ensuring respondent confidentiality.

Research improves ECG interpretation while ensuring patient data privacy.

A new framework enhances federated learning and prevents forgetfulness in AI models.

A study reveals the WordGame attack, exploiting weaknesses in LLM safety measures.

Exploring how Federated Learning can enhance data privacy in healthcare.

A novel approach improves performance and fairness in federated learning.