Decentralized paradigm in the field of cybersecurity and machine learning (ML) for the
emerging Internet of Things (IoT) has gained a lot of attention from the government …

In recent years, the Internet of Things (IoT) has made great progress. The interconnection
between IoT and the Internet enables real-time information processing and transaction …

Over the past years, the increasingly severe data island problem has spawned an emerging
distributed deep learning framework—federated learning, in which the global model can be …

The emerging technologies, such as smart sensors, 5G/6G wireless communication, artificial
intelligence, etc., have been maturing the future Internet of Things (IoT) by connecting the …

Similarity query over time series data plays a significant role in various applications, such as
signal processing, speech recognition, and disease diagnosis. Meanwhile, driven by the …

The Internet of Things (IoT) is becoming a pervasive technology entangled in everyday life.
The objective of IoT is to provide ubiquitous access to numerous devices and machines on …

Vertical federated learning (VFL) is a promising category of federated learning for the
scenario where data is vertically partitioned and distributed among parties. VFL enriches the …

The sixth-generation (6G) communication technology has been attracting great interests
from both industry and academia, as it is regarded as a promising approach to achieve more …

The advance of cloud computing has driven a new paradigm of outsourcing large-scale data
and data-driven services to public clouds. Due to the increased awareness of privacy …

Similarity queries, giving a way to disease diagnosis based on similar patients, have wide
applications in eHealthcare and are essentially demanded to be processed under fine …