With the rapid development of low-cost consumer electronics and pervasive adoption of next
generation wireless communication technologies, a tremendous amount of data has been …

Federated learning is a promising learning paradigm that allows collaborative training of
models across multiple data owners without sharing their raw datasets. To enhance privacy …

Abstract Federated Learning (FL, or Collaborative Learning (CL)) has surely gained a
reputation for not only building Machine Learning (ML) models that rely on distributed …

In this article, aiming at a Chinese keyword-based book search service, from a technological
perspective, we propose to modify a user query sequence carefully to confuse the user …

The Industrial Internet of Things (IIoT) is the essential component of Industry 4.0. Blockchain
is a promising technology for secure data sharing and trustable cooperation between IIoT …

Federated Learning (FL) is an increasingly popular form of distributed machine learning that
addresses privacy concerns by allowing participants to collaboratively train machine …

In cross-silo federated learning, clients (eg, organizations) collaboratively train a global
model using private local data. In practice, clients may be not only collaborators but also …

Social metaverse is a shared digital space combining a series of interconnected virtual
worlds for users to play, shop, work, and socialize. In parallel with the advances of artificial …

Federated learning is a popular framework designed to perform the distributed machine
learning while protecting client privacy. However, the heterogeneous data distribution in real …

In recent years, privacy and security concerns in machine learning have promoted trusted
federated learning to the forefront of research. Differential privacy has emerged as the de …