A Proposal for a Zero-Trust-Based Multi-Level Security Model and Its Security Controls

The rapid advancement of technology and increasing data utilisation have underscored the need for new models to manage and secure big data effectively. However, the constraints of isolated network environments and the limitations of existing security frameworks hinder the adoption of cutting-edge technologies such as AI and cloud computing, as well as the safe utilisation of data. To address these challenges, this study proposes an enhanced security model that integrates the concepts of Multi-Level Security (MLS) and Zero Trust (ZT). The proposed model classifies data into the following three sensitivity levels: “Classified”, “Sensitive”, and “Open”. It applies tailored security requirements and dynamic controls to each level, enhancing both data security and usability. Furthermore, the model overcomes the static access control limitations of MLS by incorporating ZT’s automated dynamic access capabilities, significantly improving responsiveness to anomalous behaviours. This study contributes to the design and evaluation of a new security model that ensures secure data protection and utilisation, even in isolated network environments such as those of military and governmental organisations. It also provides a foundation for the future development of advanced security frameworks.