The past four years have witnessed the rapid development of federated learning (FL).
However, new privacy concerns have also emerged during the aggregation of the …

Blockchain offers an innovative approach to storing information, executing transactions,
performing functions, and establishing trust in an open environment. Many consider …

Privacy protection has been an important concern with the great success of machine
learning. In this paper, it proposes a multi-party privacy preserving machine learning …

Data privacy concerns are increasing significantly in the context of the Internet of Things,
cloud services, edge computing, artificial intelligence applications, and other applications …

This work describes a fast fully homomorphic encryption scheme over the torus (TFHE) that
revisits, generalizes and improves the fully homomorphic encryption (FHE) based on GSW …

The Internet of Things (IoT) now permeates our daily lives, providing important measurement
and collection tools to inform our every decision. Millions of sensors and devices are …

Cloud computing and cloud storage have contributed to a big shift in data processing and its
use. Availability and accessibility of resources with the reduction of substantial work is one of …

In recent years, the privacy issue in Vehicular Edge Computing (VEC) has gained a lot of
concern. The privacy problem is even more severe in autonomous driving business than the …

Trusted Execution Environments (TEEs) have been widely used in many security-critical
applications. The popularity of TEEs derives from its high security and trustworthiness …

Legacy encryption systems depend on sharing a key (public or private) among the peers
involved in exchanging an encrypted message. However, this approach poses privacy …