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Information × Registration Number 0225U001384, (0121U113613) , R & D reports Title Methodology for detecting malicious processes in information systems of organizations popup.stage_title Методологія виявлення шкідливих процесів в інформаційних системах організацій Head Haidur Halyna I., Доктор технічних наукHakhov Serhii O., Кандидат військових наукDovzhenko Nadiia M., Кандидат технічних наук Registration Date 30-01-2025 Organization State University of Telecommunications popup.description1 Increasing the level of protection's processes of functioning of the information system of the organization on the basis of identification and diagnosis of harmful processes popup.description2  Modern organizations cannot do without information technologies. However, along with the advantages, IT also brings significant cyber risks when using them. Cyber ​​threats can lead to the loss of confidential information, disruption of the normal operation of the organization's information system and cause significant financial losses. The research work solves a scientific problem, which consists in developing a methodology for increasing the level of security of the organization's information system based on the identification and diagnosis of malicious processes. To protect against such threats, it is necessary to implement effective security systems. One of the key elements of such a system is monitoring the state of the logical object of the information system, which will allow timely detection of any deviations from normal operation and take the necessary measures. The work proposes a methodology for identifying and diagnosing malicious processes using machine learning methods. The methodology consists in detecting malicious processes in the network traffic of organizations based on machine learning methods, in particular, based on the support vector method (SVM), and rule-based systems. The methodology is based on the requirements for the creation and application of systems for detecting malicious processes in the network traffic of organizations, to which additional requirements are put forward that ensure trust in these systems and confidence in their functioning results. Promising areas of further research include the development of methods for detecting various types of malicious processes in the organization's information system, which will use various machine learning methods. ATTACK, THREATS, METHODOLOGY, METHOD, LOGICAL OBJECT, INFORMATION SYSTEM, IDENTIFICATION, DIAGNOSIS, HARMFUL PROCESS, FINITE AUTOMATION, MACHINE LEARNING, CORRELATION, SUPPORT VECTOR METHOD, CHOICE OF PRINCIPAL COMPONENTS, RULES Product Description popup.authors Boiko Anna O. Borsukovskyi Yurii V. Hamza Dmytro Ye. Hanchenko Mariia I. Svitlana V. Kazmirchuk Kozhukhivskyi Andrii D Korovaichenko Yurii Yu. Kuzmenko Andrii O. Marchenko Vitalii V. Sych Mykola V. Smoliev Yevhen S. Khaver Aniuta V. Shulimova Dar'ia D. popup.nrat_date 2025-01-30 Close