An Adaptive Cybersecurity Framework Integrating Machine Learning, Zero Trust Policy, and Blockchain for Academic Cloud Environments

Abstract

Cloud-based academic environments such as Learning Management Systems (LMS), Open Journal Systems (OJS), institutional repositories, and web applications face increasing cybersecurity challenges due to heterogeneous users, distributed services, and extensive exposure to public networks. Existing security approaches remain fragmented, where machine learning focuses on threat detection, Zero Trust Architecture (ZTA) emphasizes access control, and blockchain is primarily used for secure logging. The lack of integration among these components limits the ability of security systems to adapt dynamically to evolving cyber threats. This study proposes an Adaptive Cybersecurity Framework (ACF) that integrates unsupervised machine learning-based anomaly detection, a risk-based Zero Trust Policy Engine, and blockchain-based immutable audit logging within a continuous adaptive feedback loop. The framework was evaluated using 450,000 anonymized HTTP and Web Application Firewall (WAF) events collected from a multi-domain academic cloud environment consisting of LMS, OJS, repositories, and supporting web applications. The analysis revealed structured and repetitive attack behaviors dominated by automated endpoint probing and cross-domain propagation patterns, indicating ecosystem-level security threats. The proposed risk assessment mechanism demonstrated effective alignment between anomaly detection and policy-based decision making. Experimental results achieved an AUROC of 0.7296 for risk-based threat detection while maintaining an average decision latency of approximately 11 ms, indicating suitability for real-time deployment. Blockchain integration further provided verifiable, tamper-resistant audit trails for mitigation actions and policy enforcement activities. This study contributes an ecosystem-aware adaptive cybersecurity paradigm that bridges threat detection, policy enforcement, and auditability through a unified security architecture for Academic Cloud Environments.