Recent years have witnessed an exponential increase in the use of mobile and embedded
devices. With the great success of deep learning in many fields, there is an emerging trend …

Generative Adversarial Networks (GANs) are a remarkable creation with regard to deep
generative models. Thanks to their ability to learn from complex data distributions, GANs …

Although federated learning offers a level of privacy by aggregating user data without direct
access, it remains inherently vulnerable to various attacks, including poisoning attacks …

Edge intelligent computing is widely used in the fields, such as the Internet of Medical
Things (IoMT), which has advantages, including high data processing efficiency, strong real …

While federated learning (FL) is a well-known privacy-preserving (PP) solution, recent
studies demonstrate that it still has privacy problems and vulnerabilities, particularly in the …

In recent years, the privacy issue in Vehicular Edge Computing (VEC) has gained a lot of
concern. The privacy problem is even more severe in autonomous driving business than the …

The Internet of Vehicles (IoV) is a promising branch of the Internet of Things. IoV simulates a
large variety of crowdsourcing applications, such as Waze, Uber, and Amazon Mechanical …

Home appliance manufacturers strive to obtain feedback from users to improve their
products and services to build a smart home system. To help manufacturers develop a smart …

Lane detection in driving scenes is an important module for autonomous vehicles and
advanced driver assistance systems. In recent years, many sophisticated lane detection …

Federated learning has emerged as an advanced privacy-preserving learning technique for
mobile edge computing, where the model is trained in a decentralized manner by the clients …