Факультет комп’ютерних та інформаційних технологій
Постійне посилання на фондhttps://repository.lntu.edu.ua/handle/123456789/49
Переглянути
3 результатів
Результати пошуку
Item type:Наукова стаття, Multiprocessing as a Way to Optimize Queries. Advances in Transdisciplinary Engineering(2024) Khrystynets, Natalia; Melnyk, Kateryna; Lavrenchuk, Svitlana; Miskevych, Oksana; Kostiuchko, SerhiiDeveloping an effective web application involves the use of various methods and techniques to ensure fast and efficient processing of requests. Sometimes it is not possible to solve the problem of multiprocessing with a single tool, such as a programming language or framework. This work investigates the use of asynchronous methods of processing requests using queues. Job operation in background and non-background modes relative to the main web process is studied. Analytics are provided to analyze a web application with 13,000 requests to process daily. It is proposed to optimize the processing by using the Laravel framework and the Python server dual-tasking using the Supervisor tool on Linux, as well as using a task scheduler for each task. The paper presents positive findings about this algorithm, which contributes to the efficiency of web development and provides a great user experience on the website. Fast processing of web application requests can be a valuable competitive advantage for a business or organization. Research in this field helps to maintain their high competitiveness. In addition, the study of query processing speed is important in scientific research, as it contributes to the development of new algorithms, optimization methods and technologies.Item type:Наукова стаття, Effective Content Moderation Using Modern AI Tools(2024) Bortnyk, Kateryna; Bahniuk, Nataliia; Kondius, Inna; Melnyk, Kateryna; Melnychuk, Yuliia; Kondius, KostiantynIn the paper we develop a web application that integrates AI capabilities for content moderation, while providing an effective and balanced user protection system based on general comparative analysis of two leading tools for content moderation: Microsoft Content Moderator and Google Perspective API. Moderation mechanisms using AI algorithms have been developed, allowing not only to filter unwanted content, but also to adapt to changing conditions and user needs. We present the comparison results of two language models of Google Perspective API and Microsoft Content Moderator and appropriate tools taking into account the specific helpful, honest, harmless criteriums that is aligned with human values and include emotional tonality supported by developers.Item type:Наукова стаття, Threats detection and analysis based on SYSMON tool(2023) Bahniuk, Nataliia; Linchuk, Oleksandr; Bortnyk, Kateryna; Kondius, Inna; Melnyk, Kateryna; Kondiu, KostiantynIn this work, an nalysis for the study of threats in a real environment with the possibility of conducting a fullfledged analysis of threats, as well as their simulationhas been developed for research purposes. Designed laboratory was built for the threats research, specification of deploying and configuring Sysmon, imitation of an attack in laboratory conditions and its investigation by implicit signs, the processesing of threat analysis using the Sysmon tool. We present a system based on the analysis of continuous input chan-nels of Sysmon logs. The system is based on the Cyber Threat Analysis Ontology and analyzes SYSMON logs to classify software according to different threat levels and enhance cyber defense capabilities with situational awareness, prediction and auto-mated actions. The developed laboratory improves the effectiveness of threat analysis using the Sysmon tool, makes study of threats, deploying and configuring Sysmon, imitation of an attack in laboratory conditions and its investigation by implicit signs. It can be applied for the study of threats in a real environment with the possibility of conducting a full-fledged analysis of threats, as well as their simulation for research purposes.