Study of the dynamic variation in the security level of an information protection system

The rapid informatization of public life has resulted in a sharp increase in the number and complexity of cyberattacks, which inflict substantial material and reputational losses on both individuals and large organizations. Cybercriminals are progressively sophisticating their attack methods, particularly through the application of emergent technologies like artificial intelligence and machine learning. This trend poses a heightened threat to the integrity of information systems and the safeguarding of sensitive data. Consequently, there is a critical need to promptly identify the influence of dominant factors on the security level of information protection systems. To effectively address this problem, the present study investigates the combined effects of key concepts on a fuzzy cognitive map by applying the framework of dynamic causal algebra. The process dynamics in this case are shaped by the introduction of a nominal time, which enables the determination of the process stabilization point and the analysis of the effects of controlling concepts on the target at specific moments. In addition to the adjacency matrix that defines the cognitive map under consideration, the model includes three essential vector parameters: a vertex state vector representing node activity; an input influence vector initiating the activation process; and a threshold vector that filters out minor effects and remains invariant over time. Based on all activated paths, the indirect impacts of conceptual elements on the system's information security level are computed. The analysis of the obtained results is intended to ensure the reliable and stable operation of the security system. Furthermore, it will contribute to developing an effective strategy for preventing cyberattacks.