Federated learning (FL) is a kind of distributed machine learning framework, where the
global model is generated on the centralized aggregation server based on the parameters of …

Anonymization is a practical solution for preserving user's privacy in data publishing. Data
owners such as hospitals, banks, social network (SN) service providers, and insurance …

Modern cyber physical systems (CPSs) has widely being used in our daily lives because of
development of information and communication technologies (ICT). With the provision of …

The successful training of deep learning models for diagnostic deployment in medical
imaging applications requires large volumes of data. Such data cannot be procured without …

Applications of Blockchain (BC) technology and Cyber-Physical Systems (CPS) are
increasing exponentially. However, framing resilient and correct smart contracts (SCs) for …

The development of Internet of Things (IoT) brings new changes to various fields.
Particularly, industrial IoT (IIoT) is promoting a new round of industrial revolution. With more …

The confidential data is mainly managed by creating passwords, tokens, and unique
identifiers in an authorized manner. These records must be kept in a safe location away from …

The increasing volume of personal and sensitive data being harvested by data controllers
makes it increasingly necessary to use the cloud not just to store the data, but also to …

Cloud computing is a long‐standing dream of computing as a utility, where users can store
their data remotely in the cloud to enjoy on‐demand services and high‐quality applications …

Shortly after it was first introduced in 2006, differential privacy became the flagship data
privacy definition. Since then, numerous variants and extensions were proposed to adapt it …