With the development of intelligent networks such as the Internet of Things, network scales
are becoming increasingly larger, and network environments increasingly complex, which …

Compressive sensing (CS) has become a popular signal processing technique and has
extensive applications in numerous fields such as wireless communications, image …

Applications today rely on cloud databases for storing and querying time-series data. While
outsourcing storage is convenient, this data is often sensitive, making data breaches a …

Many IoT botnets that exploit vulnerabilities of IoT devices have emerged recently. After
taking over control of IoT devices, the botnets generate tremendous traffic to attack target …

In the age of the industrial big data, there are several significant problems such as high-
overhead data acquisition, data privacy leakage, and data tampering. Fog computing …

In the presence of several critical issues during data acquisition in industrial-informatics-
based applications, like Internet of Things (IoT) and smart grid, this article proposes a novel …

Physical-layer key generation is promising in establishing a pair of cryptographic keys for
emerging LoRa networks. However, existing key generation systems may perform poorly …

Abstract The blooming Internet of Things (IoTs) devices have brought many new types of
sensing applications and methods to the traditional cloud-enabled IoTs framework. Hence …

In this paper, we design the multi-class privacy-preserving cloud computing scheme (MPCC)
leveraging compressive sensing for compact sensor data representation and secrecy for …

Federated learning (FL) is a popular distributed learning framework that is proposed to
address privacy concerns in traditional machine learning. However, recent research has …