Future Internet, Volume 17, Issue 2

Generating high-quality synthetic data is essential for advancing machine learning applications in financial time series, where data scarcity and privacy concerns often pose significant challenges. This study proposes a novel hybrid architecture that...

In today’s business landscape, artificial intelligence (AI) plays a pivotal role in shopping processes and customization. As the demand for customization grows, virtual reality (VR) emerges as an innovative solution to improve users’ perc...

Insider threats pose a significant challenge to organizational cybersecurity, often leading to catastrophic financial and reputational damages. Traditional tools such as firewalls and antivirus systems lack the sophistication needed to detect and mit...

The advancement of Internet of Things (IoT), robots, drones, and vehicles signifies ongoing progress, accompanied by increasing complexities and challenges in forensic investigations. Globally, investigators encounter obstacles when extracting eviden...

In recent years, we have witnessed the era of IoT. Extensions of the IoT are found almost everywhere in the modern world: under the ground, on the ground, under the sea, in the sky, and in space. Such a rapid proliferation has given rise to a variety...

Lighting Systems (LSs) play a fundamental role in almost every aspect of human activities. Since the advent of lights, both academia and industry have been engaged in raising the quality of the service offered by these systems. The advent of Light Em...

The rapid advancement of edge computing and Tiny Machine Learning (TinyML) has created new opportunities for deploying intelligence in resource-constrained environments. With the growing demand for intelligent Internet of Things (IoT) devices that ca...

Industry-wide IoT networks have altered operations and increased vulnerabilities, notably DDoS attacks. IoT systems are decentralised. Therefore, these attacks flood networks with malicious traffic, creating interruptions, financial losses, and avail...

Training deep learning models collaboratively on decentralized edge devices has attracted significant attention recently. The two most prominent schemes for this problem are Federated Learning (FL) and Split Learning (SL). Although there have been se...

In the rapidly evolving landscape of telecommunications, the integration of commercial 5G solutions and the rise of edge computing have reshaped service delivery, emphasizing the customization of requirements through network slices. However, the hete...