Modeling and Analysis of Key Management Security Factors for Organizational Data Protection: A Multi-Source Approach

Abstract

Despite a wealth of technically advanced outcomes and strategic efforts, managing information security continues to be a persistent and complex challenge for organizations. The dynamic nature of hierarchical data security is heavily dependent on a range of interrelated factors that must be aligned effectively. For data security administrators, it is crucial not only to identify relevant data but also to understand and manage the interdependencies among various security factors. The primary objective of this study is to develop a comprehensive model of key Management Security Factors (MSFs) essential for ensuring hierarchical data safety. Initially, an extensive literature review was conducted, involving a systematic and open-coding analysis of 136 academic and industry papers. This process led to the identification of critical variables influencing data security. These variables were organized into 12 major categories: physical security, system vulnerabilities, technical infrastructure, awareness, access control, risk management, organizational resources, internal organizational dynamics, confidentiality-integrity-availability (CIA), business continuity, security governance, compliance, and policy frameworks. Subsequently, interviews with 19 industry experts were conducted to validate the practical significance of these components and to explore how they interact with one another in real-world environments. The result was a detailed visual representation that highlights both direct and indirect key-security indicators. Direct indicators have a measurable impact on the security posture of an organization, while indirect indicators influence security through interconnected pathways. This model serves as a valuable decision-making tool, enabling data security leaders to address core and peripheral factors more effectively and ensure a robust and adaptive security management strategy.