OPTIMIZATION OF DATA STORAGE IN COMPUTER ATTACK SYSTEMS AND TOOLS TAKING INTO ACCOUNT THE HISTORICAL ASPECT OF THEIR USE

Abstract

The article considers the task of increasing the effectiveness of systems and means of countering computer attacks due to the improvement of data processing and optimization processes in memory subsystems. The relevance of the study is due to the constant growth of cyber-monitoring data volumes, the increasing complexity of modern computer attacks, and the need to ensure prompt access to relevant information for timely detection of threats and decision-making to counter them.

The purpose of the work is to develop a data optimization method based on self-learning of the system memory subsystem and countermeasures against computer attacks, which provides adaptive management of the structure, placement and use of information resources in conditions of dynamic changes in the parameters of the information environment.

The proposed method, in contrast to existing approaches, provides comprehensive optimization of initial, accumulated, used data and data of fraudulent systems, taking into account the criteria of resource efficiency, data structure, layered placement, hardware and network distribution, and the specifics of the functioning of cyber protection systems. This makes it possible to reduce the redundancy of information arrays, increase the speed of access to critically important information, and improve the informativeness of the information environment.

To evaluate the effectiveness of the method, experimental studies were conducted, within which the influence of the level of data optimization on the time of access to critical information, the speed of the system's response to computer attacks and the accuracy of their detection were analyzed. The results of the experiments confirmed the presence of a stable dependence between the level of data optimization and the integral indicators of the effectiveness of the system against computer attacks.

The obtained results confirm that the use of the proposed method provides an increase in the speed of access to relevant data, a reduction in the response time to threats, and an improvement in the accuracy of detection of computer attacks. The practical significance of the work lies in the possibility of using the proposed method as a component of the adaptive architecture of data processing in modern systems and means of cyber protection.

The development of the architecture of tools and the method of data selection in corporate network protection systems is defined as promising directions for further research.