Paruchuri, Arjun Kumar (2025) Identity-first security architecture: Leveraging Microsoft Entra ID and Intelligent automation for enterprise digital transformation. World Journal of Advanced Engineering Technology and Sciences, 15 (3). pp. 1539-1546. ISSN 2582-8266
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Abstract
The evolution of enterprise security architectures has shifted from traditional network perimeter defenses to identity-centric models that recognize users, devices, and contextual signals as primary security boundaries. Microsoft's integrated cloud ecosystem, Entra ID, Power Platform, and Microsoft Defender, exemplifies this transformation by establishing identity as the foundational control plane for security and operational automation. This convergence enables organizations to implement dynamic Conditional Access policies that adapt to real-time risk assessments while simultaneously orchestrating complex business workflows through Power Automate and AI Builder. Integrating cognitive services and machine learning capabilities within these platforms facilitates intelligent document processing, automated threat response, and predictive security measures that scale with organizational complexity. By unifying identity governance with process automation, enterprises achieve enhanced security postures while reducing manual operational overhead through automated employee lifecycle management, risk-based approval workflows, and AI-driven compliance monitoring. The synergy between identity management and intelligent automation represents a fundamental shift in how organizations conceptualize and implement digital transformation strategies, moving beyond siloed security tools toward holistic, adaptive systems that respond dynamically to emerging threats and business requirements.
Item Type: | Article |
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Official URL: | https://doi.org/10.30574/wjaets.2025.15.3.1051 |
Uncontrolled Keywords: | Microsoft Entra ID; Zero Trust Architecture; Intelligent Process Automation; Power Platform; Identity-Centric Security |
Depositing User: | Editor Engineering Section |
Date Deposited: | 16 Aug 2025 13:12 |
Related URLs: | |
URI: | https://eprint.scholarsrepository.com/id/eprint/4744 |