## 1 Introduction  
The rise of smart systems brings ethical concerns as cyber-physical infrastructure becomes vulnerable to failures. These hazards include privacy breaches, system disruptions, and significant economic and human losses [1, 2, 3]. Without strong computer and network security, technology endangers personal privacy and increases the likelihood of severe social and financial consequences [4]. Numerous global systems and databases face constant attacks, particularly targeting privacy and authentication mechanisms [5]. Thus, several models highlight the benefits of multilevel security achieved through a three-layer system, using three security evaluations to enhance protection and ensure thorough coverage. Various algorithms and models in cybersecurity, such as Rivest-Shamir-Adleman(RSA) [6], Elliptic Curve Cryptography (ECC) [7], and Advanced Encryption Standard (AES) [8], are designed to detect security threats, anomalies, and fraud by effectively correlating information. These can be integrated with multilevel security to develop optimal authentication and standard models. To address the question of what is most important when selecting multilevel security for authentication and data communication, as proposed by [9], several factors are considered and addressed when selecting and generating these types of models. The term \"multilevel security\" is used to describe the requirement of defining multiple categories or levels of data. However, the significance of a semantic for multilevel models cannot be overstated, as it has the potential to decrease the number of tuples inside relations and minimize the existence of numerous versions of reality across different security levels [9]. The primary motivation of this study is to develop a newly generated multilevel secure model to assist developers in creating systems for big data. This model aims to provide the most effective authentication methods, apply robust user restrictions, and safeguard systems from attacks and vulnerabilities across various domains, such as economics, politics, healthcare, and others. The essential requirement for ensuring the security of a system is the existence of a clear set of guidelines that define which subjects are authorized to access exact objects [10]. \"Access\" is a fundamental notion, signifying the transmission of information either from a subject to an object or from an object to a subject. For instance, when a user (acting as a subject) updates the dataset (functioning as an object), information is transferred from the subject to the object. When a user retrieves a record from a dataset, information is transferred from the object to the subject, as highlighted in the following key points:  
* Multilevel security facilitates the categorization of both data and users according to a hierarchical system of security levels provided. * Database management systems are designed to facilitate the storage, organization, and modification of data in a manner that allows for efficient access and management. * A multilevel secure approach ensures that a DBMS implements a system allowing access to the database only for authorized users. * The information is divided into classes and users are able to be given permission to view particular types of data. Although multiple types or levels of data are established, such a requirement has been referred to using the term multilevel security. * The approach is to reduce time consumption during the authentication process while maintaining security mechanisms. * Multilevel points can be integrated with cybersecurity algorithms to enhance system performance during the process. The strategy for designing a new Multilevel Security/Database Management System (MLS/DBMS) structure includes detailed approaches for distributing data models. This approach is introduced to implement multilevel security and support the development of a DBMS prototype.