Latest Articles for Data Privacy

New algorithms enhance model performance in federated learning through effective client clustering.

Investigating privacy over-collection in WeChat's increasingly popular sub-apps.

A new framework integrates privacy and robustness techniques for trustworthy machine learning.

A new approach enhances privacy while optimizing collaborative agent performance.

New methods enhance personalized federated learning while preserving data privacy.

Learn how deep learning models process encrypted images while maintaining privacy.

A new benchmark for combining data types while prioritizing user privacy.

A new method protects individual privacy in sharing mobility data during crises.

A study on linking fine-tuned models to their base versions.

Fedstellar enables secure and efficient training of machine learning models across devices.

A new framework improves learning from limited data in federated environments.

Financial institutions seek secure ways to share data while protecting privacy.

HePCo enhances continual federated learning, prioritizing privacy and efficiency.

Discover how edge learning enhances IoT security and performance in advanced networks.

Utilizing both private and public data enhances machine learning while ensuring privacy.

This article discusses techniques for achieving accuracy and privacy in machine learning models.

Learn how cuckoo hashing enhances data storage and privacy in cryptographic applications.

New techniques improve the speed and efficiency of encrypted computations using GPUs.

A new benchmark called FedNoisy helps tackle noisy labels in federated learning.

RQM enhances privacy in federated learning while maintaining model efficiency.

New dataset improves violence detection while protecting privacy using DVS cameras.

New views help code reviewers manage personal data in software efficiently.

FDINet offers a new defense against model extraction attacks in cloud-based services.

Discussing the vital need for AI regulation and its implications for society.

New protocols improve privacy and model integrity in federated learning.

MimiC enhances federated learning by addressing the dropout issue for better model accuracy.

A closer look at the problems with the RVL-CDIP benchmark dataset.

FLGo platform streamlines federated learning for researchers with flexible tools.

A new method improves low-dose CT imaging while protecting patient data.

DOF-ID enhances threat detection without compromising data privacy.

Examining the intersection of AI image generation and copyright risks.

A new algorithm improves decentralized learning as data evolves.

A novel approach enhances defenses in federated learning systems against adversarial attacks.

Examining the impacts of federated learning on model generalization and data privacy.

SBNNs improve efficiency in machine learning for resource-limited devices.

A look at decentralized deep learning approaches that prioritize data privacy.

Examining the balance between privacy and fairness in federated learning models.

A new method improves federated learning performance amid data privacy concerns.

A new algorithm improves decentralized learning's resilience against attacks.

A new method improves medical image classification while protecting patient data.