Abstract
The rapid development of ICT caused significant changes in the ways and means of communication between people using network technologies. Creating, storing, distributing, and sharing information is becoming increasingly easy and accessible. Today, one of the most promising technologies for storing information and providing effective online services is the use of cloud systems. Using this technology to protect computer systems from cyberattacks can bring many advantages compared to traditional protection schemes. However, the rapid evolution of malicious software and the diversification of its types leads to a significant increase in the vulnerabilities of the implementation of attacks on information resources, especially on objects of the state’s critical infrastructure. Thus, there is a need to develop new methods and models for effective data processing in cloud-based malware detection systems. In this study, the information technology model for efficient data processing in cloud-based malware detection systems was developed, which considers the need to formulate commands for transferring control to the ICT software client. In addition, a study of the probabilistic and temporal characteristics of algorithms and programs for generating and processing metadata in a cloud-based malware detection system was conducted. This allowed for increasing the accuracy of the results of estimation of time characteristics by up to 1.7 times and jitter characteristics by up to 4.5 times.