This research introduces a novel behavior-based malware detection framework that leverages recurrent neural networks with temporal attention. The model effectively captures malicious process behaviors over time, increasing detection accuracy and minimizing false positives in complex cybersecurity environments.

Julian Patrick Simmons, Olivia Beatrice Turner, Samuel Henry Collins, Isabelle Sophia Webb, Arthur James Mitchell

This study presents a zero-trust framework for microservices using decentralized identity systems and intelligent policy proxies. The proposed architecture enhances access security in distributed environments by enforcing per-request authentication and authorization at microservice entry points.

Clara Evelyn Sharp, Benjamin Oscar Fletcher, Lucy Matilda Andrews, Edward Harrison Payne, Florence Harriet Barker

The paper proposes a hybrid security system combining blockchain-based audit trails and AI-enabled intrusion response. Designed for cloud infrastructures, the model ensures tamper-proof logging and real-time automated countermeasures against detected breaches, significantly enhancing data protection and compliance transparency.

Theodore Isaac Franklin, Georgia Rose Baxter, Sebastian Daniel Hart, Jessica Louise Walsh, Harrison Michael Blake

This study proposes novel cryptographic protocols based on lattice-based security primitives to protect cloud data transmission. The protocols are designed to remain secure against future quantum threats, enabling organizations to transition toward post-quantum resilience in cloud infrastructure.

Louis Zachary Bennett, Victoria Daisy Ferguson, Thomas George Yates, Amelia Rose Chapman, William Charles Howell

This paper presents a privacy-preserving federated learning framework for healthcare data analysis. By combining encrypted gradient exchanges with differential privacy, the model enables collaborative analytics without exposing sensitive patient information, ensuring both performance and regulatory compliance across institutions.

Matthew Joseph Coleman, Harriet Louise Douglas, Oscar William Hunt, Molly Grace Chapman, Alexander Edward Knight

This study introduces an intelligent cryptographic key management framework tailored for smart cities. It combines lightweight encryption with AI-driven key revocation, optimizing security for resource-constrained IoT nodes while maintaining integrity and availability in large-scale urban network deployments.

Chloe Alexandra Warren, Nathan Elijah Wilkinson, Emily Charlotte Hayes, James Oliver Barrett, Megan Isabelle Gilbert

This paper analyzes adversarial threats targeting cloud-hosted intrusion detection systems and proposes countermeasures using ensemble defense models. The approach detects manipulated inputs while preserving detection accuracy, ensuring robust and adaptive threat intelligence for cloud security infrastructures.

Daniel Frederick Holmes, Lucy Amelia Mason, Leo Jonathan Fisher, Alice Georgia Hammond, Joseph Samuel Mills

We propose a blockchain-integrated secure multi-party computation protocol for health data analytics in federated settings. The framework ensures data confidentiality and auditability across multiple healthcare entities without compromising individual data ownership or compliance with privacy regulations.

Freddie Thomas Baldwin, Eleanor Rose Pearson, Isaac William Rowe, Sophie Elizabeth Quinn, George Alexander Harvey