INFORMATION SECURITY OF OBJECTS OF DYNAMIC SCENARIO-PRECEDENTED SYSTEMS

Abstract

In modern information technology, ensuring data security is one of the most critical tasks, especially in dynamic scenario-based precedent systems. These systems are characterized by a high level of variability and complexity in the scenarios used for modeling various situations and events.This paper is dedicated to the study of information security issues for objects in dynamic scenario-based precedent systems. The paper examines the main methods and approaches to data protection, including cryptographic algorithms, intrusion detection systems, and authentication methods. Special attention is given to the analysis of threats that may arise during the operation of such systems, as well as methods for their prevention and mitigation.Based on the conducted analysis, new methods for enhancing security levels have been proposed, which are based on the use of artificial intelligence and machine learning to detect anomalies and predict potential attacks. The paper also addresses issues of ensuring data confidentiality, integrity, and availability in the context of dynamic environmental changes.The proposed approaches and methods have been tested on practical examples, demonstrating their effectiveness and feasibility for protecting information systems under dynamic conditions. The research results can be useful for software developers, security analysts, and other professionals in the field of information security.