The communication and networking field is hungry for machine learning decision-making
solutions to replace the traditional model-driven approaches that proved to be not rich …

Abstract The Internet of Things (IoT) paradigm is considerably impacted by security
challenges, which has lately demanded substantial consideration. Accordingly, certain …

As cyberattacks become more intelligent, it is challenging to detect advanced attacks in a
variety of fields including industry, national defense, and healthcare. Traditional intrusion …

Although the existing machine learning-based intrusion detection systems in the Internet of
Things (IoT) usually perform well in static environments, they struggle to preserve their …

Cloud computing is undeniably becoming the main computing and storage platform for
today's major workloads. From Internet of things and Industry 4.0 workloads to big data …

Recent advancement in vision‐based robotics and deep‐learning techniques has enabled
the use of intelligent systems in a wider range of applications requiring object manipulation …

Due to groundbreaking rise of e-commerce and growing trends of customers' environmental
mindfulness, recently, more and more manufacturers are willing to produce eco-friendly …

Federated learning is a distributed machine learning approach that enables a large number
of edge/end devices to perform on-device training for a single machine learning model …

Insider threats are a pernicious threat to modern organizations that involve individuals
intentionally or unintentionally engaging in behaviors that undermine or abuse information …

Botnets are some of the most recurrent cyber-threats, which take advantage of the wide
heterogeneity of endpoint devices at the Edge of the emerging communication environments …