This research introduces a zero trust architecture combining AI-powered policy enforcement to secure multi-tenant interactions between edge and cloud domains. It achieves dynamic access decisions based on contextual behavior analysis without relying on fixed network boundaries or predefined trust assumptions.

Marcus Leopold Whitman, Vanessa Claire Kingsley, Tobias Richard Wellstone, Fiona Margaret Armstrong, Hugo Benedict Calder

The paper explores real-time runtime threat detection mechanisms enhanced by AI to safeguard containerized applications across multi-cloud environments. It proposes lightweight models that adaptively identify behavior deviations and emerging attack signatures without interrupting container orchestration workflows.

Lawrence Edwin Bradshaw, Isla Penelope Whitford, Dominic Arthur Stratton, Matilda Eve Pembroke, Felix Jonathan Northam

This work presents a federated deep learning approach using differential privacy to detect malware in cloud systems without exposing client-side data. The model learns shared threat representations across cloud tenants while preserving user confidentiality during training.

Julian Edward Godfrey, Beatrice Florence Huxley, Sebastian Noel Calderon, Olivia Harriet Crenshaw, Douglas Nathaniel Hargrove

This study proposes an adaptive role-based encryption model tailored for healthcare cloud environments. It dynamically modifies access keys and permissions based on user behavior, improving compliance and security across distributed patient data systems in hospitals and research networks.

Archibald Rupert Finnegan, Imogen Charlotte Vance, Theodore James Berwick, Louisa Eleanor Rutherford, Elliot Charles Blackstone

This paper introduces a hybrid cryptographic framework integrating quantum-resistant algorithms with classical techniques for secure key exchange across inter-cloud platforms. The model ensures forward secrecy and protects digital assets in cross-border, jurisdiction-sensitive data exchange scenarios.

Edward Julian Southgate, Amelia Rosalind Blackwell, Oscar Maximilian Hawthorne, Phoebe Isabelle Fleetwood, Hugo Laurence Redmond

The paper introduces a graph-theoretical model for analyzing threat propagation in multi-tier cloud networks. An edge analytics engine evaluates security events in real time, optimizing detection latency and allowing scalable intrusion tracking across decentralized cloud assets and services.

Gideon Francis Holloway, Clara Vivienne Redford, Quentin Charles Langston, Matilda Evelyn Starling, Tobias Graham Prescott

This work proposes an AI-driven adaptive honeynet architecture that mimics real services in hybrid clouds. The system captures attacker strategies, predicts future behavior using deep learning models, and helps security teams refine threat response protocols dynamically.

Victor Edmund Ramsay, Penelope Iris Kingsmill, Dominic Walter Chesterton, Florence Isabelle Melrose, Edwin Charles Dunbar

This study presents a blockchain-based framework for credential issuance, revocation, and verification across federated governmental cloud infrastructures. The model increases transparency, auditability, and cross-domain trust while maintaining privacy and data integrity during secure document and service access workflows.

Leonard Alfred Beckett, Isobel Frances Wyndham, Zachary Thomas Radcliffe, Eleanor Catherine Fairfax, Hugo Dominic Pemberton