This article presents research challenges and a tutorial on performance evaluation of
blockchain-based security and privacy systems for the Internet of Things (IoT). We start by …

As the number of Internet-connected systems rises, cyber analysts find it increasingly difficult
to effectively monitor the produced volume of data, its velocity and diversity. Signature-based …

Federated learning (FL), as a distributed machine learning setting, has received
considerable attention in recent years. To alleviate privacy concerns, FL essentially …

Critical infrastructure systems are vital to underpin the functioning of a society and economy.
Due to the ever-increasing number of Internet-connected Internet-of-Things (IoT)/Industrial …

Internet-of-Things (IoT) technology is increasingly prominent in the current stage of social
development. All walks of life have begun to implement the IoT integration technology, so as …

IoT security is one of the prominent issues that has gained significant attention among the
researchers in recent times. The recent advancements in IoT introduces various critical …

Federated deep learning has been widely used in various fields. To protect data privacy,
many privacy-preservingapproaches have been designed and implemented in various …

Federated Learning (FL), emerging as a distributed machine learning, is a popular paradigm
that allows multiple users to collaboratively train an intermediate model by exchanging local …

Deep neural networks (DNNs) have shown great success in completing complex tasks.
However, DNNs inevitably bring high computational cost and storage consumption due to …

Fog-cloud computing promises many new vertical service areas beyond simple data
communication, storing, and processing. Among them, distributed deep learning (DDL) …