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Information × Registration Number 0223U001484, 0121U109936 , R & D reports Title Self-organized distributed system for malware detection in computer networks popup.stage_title Head Hovorushchenko Tetiana O., Доктор технічних наук Registration Date 28-01-2023 Organization Khmelnytskyi National University popup.description2  The object of research is the process of malware detection in computer networks (CN). The aim of the work is to increase the effectiveness of malware detection by developing theoretical foundations and creating a self-organized distributed system (SODS) for malware detection in CN. To solve the problems, the main provisions were used: (1) the theory of distributed systems (DS) to build models of the architecture of the DS and its components, on the basis of which software and hardware and software tools can be developed; (2) theories of abstract algebra to represent malware as elements of subsets with given characteristic properties, in the form of behavioral algebras; (3) set theory and graph theory for a detailed presentation of malware as research objects; (4) classification methods for assigning software objects to malware classes; (5) theories of CN to represent and organize the functioning of a DS. The following theoretical and practical results were obtained: (1) models and architectures of a SODS for malware detection were developed; (2) characteristic properties of malware are formalized and algebras of malware behavior are developed; (3) methods for detecting network and file malware in CN have been developed; (4) developed an intelligent verification agent for taking into account the information of the subject field in the process of developing a SODS for malware detection; (5) a SODS for malware detection was created, experimental studies were conducted, methods for determining the effectiveness of DS for malware detection were developed and applied. The developed SODS differs from known systems by comprehensively taking into account the requirements of distribution, decentralization, multi-level and self-organization, which will allow creating on its basis DS and their components that will function autonomously and independently make decisions about the presence of malware ensuring and increasing its functional capabilities Product Description popup.authors Bobrovnikova Kira Yu Hovorushchenko Tetiana Оleksandrivna Lysenko Serhii Mykolaiovych Savenko Oleh Stanislavovych Sachenko Anatoliy Oleksiyovych popup.nrat_date 2023-01-28 Close