This research explores the use of artificial intelligence and machine learning algorithms to enhance cybersecurity measures. It investigates their role in identifying, preventing, and mitigating emerging threats such as malware, phishing, and ransomware attacks, aiming to provide automated, adaptive security mechanisms in modern networks.

Oliver Benjamin Foster, Sarah Louise Moore, Andrew Christopher Harris, Megan Anne Walker, Michael John Brown

This paper investigates scalable cloud infrastructure models for processing and analyzing large volumes of real-time data from Internet of Things (IoT) devices. It examines the integration of cloud services with edge computing and their application in sectors such as healthcare, transportation, and industrial automation.

Daniel Christopher Miller, Mark Anthony Harris, Olivia Jane Thompson, Elizabeth Mary Carter, David Michael Brown

This paper explores how blockchain technology can enhance data security and privacy in cloud computing environments. By integrating decentralized ledger systems, it aims to address challenges like data breaches, unauthorized access, and the need for trustworthy authentication mechanisms, ensuring privacy for users and organizations.

William Joseph Taylor, Emma Louise Davis, James Edward Wilson, Olivia Grace Harris, Daniel Thomas Clark

This study focuses on optimizing cloud-based big data analytics for predictive maintenance in industrial systems. By leveraging machine learning algorithms, the paper proposes a framework to predict equipment failures, reducing downtime, maintenance costs, and enhancing the overall performance of industrial processes.

Benjamin Robert Young, Samantha Marie Walker, John Patrick Williams, Grace Victoria Taylor, Alexander Thomas Moore

This research introduces a novel edge computing framework for real-time healthcare data processing. The framework integrates IoT devices, cloud platforms, and edge computing to enable efficient data collection, storage, and analysis, enhancing real-time decision-making in healthcare applications.

David Robert Johnson, Emily Anne Martin, Lucas Samuel White, Amelia Grace Harris, Michael Thomas Scott

This paper presents a comparative study of scalable cloud-based data storage solutions for modern enterprises. It analyzes various platforms' capabilities, including cost-effectiveness, security, and scalability, offering a comprehensive guide to selecting the best solution for businesses with growing data storage needs.

Sarah Elizabeth Green, Christopher Michael Carter, John William Morgan, Laura Rose Bennett, Daniel Samuel Allen