Federated Learning (FL) is a technique that can learn a global machine-learning model at a
central server by aggregating locally trained models. This distributed machine-learning …

Machine learning has, over the decades, ushered in a dramatic transformation across a
range of sectors, including network security. Security experts agree that the potential of …

Abstract Internet-of-Things (IoT) is characterized by the incorporation of resource
constrained devices that are inter-networked in an ad-hoc manner. Given the diversity of the …

The integration of artificial intelligence has led to significant advancements across industries
but also exposed systems to security vulnerabilities. We evaluate defense methods …

We introduce FEDQ-Trust, an innovative data-driven trust prediction approach designed for
mobile edge-based Internet of Things (IoT) environments. The decentralized nature of …

Kidney stone detection is a crucial task in medical diagnostics where early identification can
mitigate severe health complications. This research employs advanced deep-learning …

Emerging technology like Internet of Things (IoT) seeks to facilitate the linking of numerous
smart devices and diverse networks. IoT enabled platform architecture heavily relies on ad …

The rapid pace of technological evolution has transformed the way we live, work, and
interact with each other. Computing and information technology play a pivotal role in driving …

Nowadays security and privacy in online networks is always questionable due to various
factors in terms of cyber security in the form of attackers present outside the network. In this …

Abstract Internet of Things (IoT) gadgets connect and simplify life in several ways. The
independence of these technologies poses some issues, such as the protection of security …