⏩ Volume 23, Issue No.1, 2025 (CNI)
Blockchain-Enabled Access Control Mechanisms for Decentralized Data Sharing in Secure Healthcare Networks

This paper proposes a blockchain-integrated access control model that secures data exchange in healthcare networks. Utilizing decentralized identifiers and smart contracts, the approach enhances privacy and auditability across distributed systems managing sensitive medical records.

Victor Emmanuel Langston, Lucy Miranda Hawthorne, Noah Elijah Carrington, Yuki Mei Tanaka, Oliver Zachary Pierce

Paper ID: 72523101
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A Multi-Factor Behavioral Authentication Framework for Cloud-Hosted Enterprise Applications in Zero Trust Environments

This study introduces a behavioral-based multi-factor authentication framework tailored for zero trust cloud environments. The model leverages usage patterns, location data, and biometric cues to authenticate users with enhanced precision and prevent unauthorized access.

Henry Lucas Montgomery, Claire Isabella Walsh, Benjamin Arthur Hughes, Sofia Madeleine Lawson, Wei Li Chen

Paper ID: 72523102
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A Multi-Factor Behavioral Authentication Framework for Cloud-Hosted Enterprise Security Architectures

This study introduces a behavioral-based multi-factor authentication framework tailored for zero-trust cloud enterprise models. It ensures identity integrity using passive behavioral signals, enabling seamless and secure access to mission-critical digital infrastructure.

Henry Lucas Montgomery, Claire Isabella Walsh, Benjamin Arthur Hughes, Sofia Madeleine Lawson

Paper ID: 72523103
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Resilient Blockchain-Enabled Identity Management for Cross-Border Healthcare Data Access Control

This research proposes a blockchain-integrated identity platform for healthcare systems that ensures secure patient data sharing across national borders while maintaining strict compliance with privacy regulations, utilizing smart contracts to manage access permissions dynamically.

Isabelle Renee Thornton, William Nathaniel Black, Georgia Louise Bradshaw, Oliver Graham Kendrick

Paper ID: 72523104
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AI-Driven Anomaly Detection in Network Traffic Using Temporal Graph Neural Networks for Cyber Defense

This paper presents a temporal graph neural network model that detects anomalies in network traffic for cybersecurity systems. The model learns from evolving traffic patterns, identifying malicious activities in real time, significantly improving detection accuracy compared to baseline approaches.

Leonard Bryce Matthews, Amelia Juliet Forster, Hugo Sebastian King, Eleanor Victoria Dawson, Max Elliott Carter

Paper ID: 72523105
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Federated Learning Framework for Secure Collaborative Intrusion Detection Across Distributed Edge Devices

This study introduces a privacy-preserving federated learning model for detecting cyber intrusions on distributed edge networks. It enables decentralized threat detection while maintaining data locality, improving security effectiveness in scenarios where central aggregation is not viable.

Grace Isabelle Thornton, Dominic Francis Howard, Zoe Abigail Spencer, Thomas Isaac Wilkins, Charlotte Rose Foster

Paper ID: 72523106
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Secure Multi-Tenant Cloud Architecture for Threat-Resilient Virtual Machine Isolation and Policy Enforcement

This paper proposes a cloud architecture focused on multi-tenant virtual machine isolation to prevent lateral threats. It introduces dynamic enforcement policies that respond to behavioral signals, providing robust containment and secure coexistence within virtualized cloud environments.

Frederick Owen Bishop, Emily Theresa Chambers, Nathaniel George Ellis, Chloe Margaret Reynolds, Daniel Louis Barrett

Paper ID: 72523107
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