International Journal of Computational Science, Technology and Management
E-ISSN: XXXX - XXXX

Open Access | Research Article | Volume 1 Issue 1 | Download Full Text

Secure Enterprise HR Data Governance for Cloud-Based Human Capital Systems

Authors: Chandra Sekhar
Year of Publication : 2026
DOI: XX:XXXXX:XXXXXXXX
Paper ID: IJCSTM-V1I1P104


How to Cite:
Chandra Sekhar, "Secure Enterprise HR Data Governance for Cloud-Based Human Capital Systems" International Journal of Computational Science, Technology and Management, Vol. 1, No. 1, pp. 20-24, 2026.

Abstract:
The rapid adoption of cloud-based Human Capital Management (HCM) systems has fundamentally transformed enterprise Human Resource (HR) operations by enabling centralized workforce management, real-time analytics, and scalable digital services. However, the migration of sensitive employee information to cloud platforms has introduced significant challenges related to data governance, privacy protection, regulatory compliance, and cybersecurity. Organizations increasingly rely on cloud technologies to manage recruitment, payroll, performance evaluation, employee engagement, and workforce analytics, making HR data one of the most valuable enterprise assets. Consequently, secure HR data governance has become a strategic requirement rather than merely a technical necessity. This study investigates secure enterprise HR data governance frameworks for cloud-based HCM systems by examining current governance practices, security architectures, compliance mechanisms, and emerging technologies. A qualitative research methodology based on an extensive literature review and comparative analysis of existing governance models is employed. The findings indicate that integrating governance policies with identity and access management, encryption, zero-trust architecture, artificial intelligence-based anomaly detection, and continuous compliance monitoring significantly improves the confidentiality, integrity, and availability of HR data. Furthermore, the study identifies existing research gaps concerning adaptive governance, cross-cloud interoperability, and AI-assisted compliance automation. The proposed governance framework supports organizations in establishing secure, transparent, and regulation-compliant HR ecosystems while enhancing organizational resilience and employee trust.

Keywords: Human Capital Management, HR Data Governance, Cloud Computing, Information Security, Zero Trust Architecture, Data Privacy, Identity and Access Management, Enterprise Security.

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