This paper introduces a secure federated learning model for protecting patient data across cloud-integrated healthcare devices. The system ensures real-time anomaly detection and decentralized data privacy, strengthening resilience against breaches while promoting secure machine learning collaboration across institutions.

Tristan Howard Ellington, Olivia Charlotte Gresham, Nathaniel Rhys Middleton, Amelia Rose Hadley, Felix Jonathan Hartwell

The research designs a zero trust architecture tailored for multi-tenant clouds using software-defined perimeter (SDP) protocols. It validates enhanced control over network access, segmented workloads, and minimized lateral threats in dynamic cloud deployments.

Maxwell Julian Rivers, Charlotte Elise Pennington, Rupert Miles Hargrove, Lydia Beatrice Langley, Sebastian Hugh Ashcroft

This paper studies adversarial AI attacks against cloud-driven vision systems in autonomous transport. It proposes a hybrid anomaly-detection strategy combining entropy monitoring and gradient analysis to defend real-time object detection models deployed across interconnected smart traffic infrastructures.

Theodore James Bramley, Annabelle Grace Whitmore, Hugo Elias Carrington, Phoebe Elizabeth Temple, Dominic Arthur Tennyson

The study proposes a quantum key distribution (QKD) framework to safeguard file transfers in multi-cloud environments. Leveraging entangled photon pairs, the method ensures unbreakable encryption and intrusion detection, achieving high-speed secure exchange without key replication vulnerabilities.

Benedict Louis Redgrave, Georgina Alice Winthrop, Lucas Graham Rutledge, Helena May Davenport, Henry Isaac Belvedere

This research presents a secure API gateway orchestration model to manage data exchange among cloud-hosted SaaS ecosystems. It uses layered authentication and AI-based anomaly detection to mitigate unauthorized access, maintaining seamless operations between different enterprise service platforms.

Julian Patrick Kingsley, Florence Miranda Wilton, Edward Nathaniel Blaine, Sophie Catherine Rosenthal, Tobias Vincent Chatham

This paper presents an AI-based framework for preventing DDoS attacks within multi-tenant cloud infrastructure. Using machine learning, the system identifies abnormal traffic patterns and enhances real-time attack mitigation, ensuring the continuity and security of cloud-based services.

Oliver Theodore Baxter, Amelia Jean Hamilton, Natalie Margaret Royce, Lucas James Wetherby, Peter Daniel Southgate

The research explores blockchain technology to enable decentralized authentication in cloud storage for healthcare data. It ensures access control, enhances data integrity, and minimizes security breaches by leveraging smart contracts and distributed ledger technology.

Eliza Caroline Montgomery, Samuel Peter MacDonald, Sophia Isobel Langton, Matthew Thomas Kirk, Olivia Jane Preston