The evolution of cybersecurity is undoubtedly associated and intertwined with the
development and improvement of artificial intelligence (AI). As a key tool for realizing more …

The outsourced distributed database is frequently used to tackle the large amounts of data in
various smart city scenarios. The data partition technique is a significant research topic in …

In recent years, rare pattern mining has shown great vitality in some real-world fields, such
as disease diagnosis, criminal behavior analysis, anomaly detection in networks, and so on …

The rapid development of the Artificial Intelligence of Things (AIoT) opens up a new
perspective for emerging service-based applications and becomes a major driver of diverse …

Purpose In the digital economy era, digital platforms are vital infrastructure for innovation
subjects to perform digital innovation activities. Achieving efficient and smooth knowledge …

This paper considers the problem of differentially private vertically partitioned data sharing.
In particular, with the assistance of a semi-honest curator, the involved parties (ie, data …

The knowledge that is acquired through a learning process has ethical concerns when
shared, as there can be restrictions on the parties who can use the piece of knowledge …

With the rapid development of advanced networking and computing technologies such as
the Internet of Things, network function virtualization, and 5G infrastructure, new …

This paper contributes to the fields of Federated Learning (FL) and Industrial Cyber-Physical
Systems (ICPS) privacy. It introduces a novel model aggregation technique aimed at …

Existing literature confirms the ability of machine learning to identify fraudulent smart grid
power consumers who report false consumption readings to pay less electricity bills …