The rapid adoption of cloud-native applications, distributed analytics, edge computing, automated workflows, and machine-driven services has substantially increased the number of non-human identities (NHIs) operating within contemporary information systems. Unlike conventional human identities, NHIs include service accounts, application identities, workload credentials, automated processes, machine-to-machine connections, and other programmatic security principals. Their continuous operation, high privilege requirements, and large-scale interactions create governance challenges that conventional identity and access management approaches are not sufficiently designed to address. This research and review paper develops an automated security governance framework for NHIs in cloud Identity and Access Management (IAM), drawing theoretical and technical insights exclusively from the supplied literature on distributed computing, graph processing, parallel algorithms, machine learning, edge-cloud architectures, and data analytics. The methodology synthesizes these studies into an identity-centric governance model consisting of identity discovery, relationship modeling, risk analysis, policy evaluation, privilege optimization, continuous monitoring, and automated remediation. Graph-oriented research provides a theoretical basis for representing identities, resources, permissions, and dependencies as interconnected structures, while distributed and parallel computing studies support scalable analysis of large identity environments. The resulting framework demonstrates how automated governance can improve visibility, reduce excessive privileges, detect anomalous relationships, and support continuous security decisions. The analysis also identifies limitations related to graph complexity, dynamic cloud environments, policy interpretation, false positives, computational overhead, and incomplete identity inventories. The paper contributes a research-oriented conceptual architecture for treating NHI governance as a continuously computed security problem rather than a static access-control configuration. 

Non-Human Identities, Cloud IAM, Security Governance, Identity Graph

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Ganapathy, S. K. (2025). Automated Governance and Protection of Non-Human Identities in Cloud IAM. Frontiers in Emerging Computer Science and Information Technology, 2(02), 08–20. Retrieved from https://irjernet.com/index.php/fecsit/article/view/cloud-iam-non-human-identities.