This study attempts to explain the development and progress of the technology used for
sharing health information across health care organizations (such as hospitals and …

Federated learning (FL) provides a robust distributed framework for machine learning that
solves privacy leakage concerns. In the some cases, it is hard to train the FL model with …

Current privacy-preserving schemes proposed for distributed deep learning (DDL) are
based on public key infrastructure (PKI) which has management of keys problem and also …

Federated Learning (FL) has recently arisen as a revolutionary approach to collaborative
training Machine Learning models. According to this novel framework, multiple participants …

Blockchain has become an integral part of various IoT applications, and it has been
successful in boosting performance in various aspects. Applying blockchain as a trust …

With the increasing importance of data sharing for collaboration and innovation, it is
becoming more important to ensure that data is managed and shared in a secure and …

Healthcare transformation is becoming one of the highest priorities in a world whereby
remarkable advances in technology are taking place. Recent healthcare data fusion …

In federated learning, each participant trains its local model with its own data and a global
model is formed at a trusted server by aggregating model updates coming from these …

There are a number of real-world instances of blockchain-based systems that are being
used or suggested for medical data security, but their implementation is limited and fraught …

Blockchain technology has gained significant attention in recent years due to its
decentralized and immutable nature, and has made itself ideal for various applications such …