title: ÐÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð°Ð½Ð¾Ð¼Ð°Ð»Ð¸Ð¹ Ð² Ð±ÐµÐ·Ð¾Ð¿Ð°ÑÐ½Ð¾Ð¹ ÑÐ°Ð±Ð¾ÑÐµ Ð¾Ð¿ÐµÑÐ°ÑÐ¸Ð¾Ð½Ð½ÑÑ ÑÐ¸ÑÑÐµÐ¼ Ñ Ð¿Ð¾Ð¼Ð¾ÑÑÑ Ð³ÑÐ°ÑÐ¾Ð²ÑÑ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÑ ÑÐµÑÐµÐ¹
title: Ð²ÑÐ¿ÑÑÐºÐ½Ð°Ñ ÐºÐ²Ð°Ð»Ð¸ÑÐ¸ÐºÐ°ÑÐ¸Ð¾Ð½Ð½Ð°Ñ ÑÐ°Ð±Ð¾ÑÐ° Ð¼Ð°Ð³Ð¸ÑÑÑÐ°
titleType: Subtitle
title: Predicting anomalies in the secure operation of operating systems using graph neural networks
Creators: name: ÐÐ²Ð°Ð½Ð¾Ð²Ð°, ÐÐ»ÑÐ³Ð°
Publisher: name: Ð¡Ð°Ð½ÐºÑ-ÐÐµÑÐµÑÐ±ÑÑÐ³ÑÐºÐ¸Ð¹ Ð¿Ð¾Ð»Ð¸ÑÐµÑÐ½Ð¸ÑÐµÑÐºÐ¸Ð¹ ÑÐ½Ð¸Ð²ÐµÑÑÐ¸ÑÐµÑ ÐÐµÑÑÐ° ÐÐµÐ»Ð¸ÐºÐ¾Ð³Ð¾
Year: 2024
Subjects: Ð²ÑÑÐ²Ð»ÐµÐ½Ð¸Ðµ Ð°Ð½Ð¾Ð¼Ð°Ð»Ð¸Ð¹
Ð¿ÑÐ¾Ð³Ð½Ð¾Ð·Ð¸ÑÐ¾Ð²Ð°Ð½Ð¸Ðµ Ð°Ð½Ð¾Ð¼Ð°Ð»Ð¸Ð¹
Ð³ÑÐ°ÑÐ¾Ð²ÑÐµ Ð½ÐµÐ¹ÑÐ¾Ð½Ð½ÑÐµ ÑÐµÑÐ¸
Ð³ÑÐ°ÑÐ¾Ð²ÑÐµ ÑÐµÑÐ¸ Ð²Ð½Ð¸Ð¼Ð°Ð½Ð¸Ñ
anomaly detection
anomaly forecasting
graph neural network
graph attention network

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description: The purpose of the study is to ensure the security of operating systems by identifying anomalies in their operation using graph neural networks. The subject of the work research is anomalies in operating systems and methods for their detection and prediction. The research set the following goals: 1. Analysis of types of security anomalies in operating systems and systematization of methods for their prediction. 2. Analysis of the main types of graph neural networks. 3. Development of a method for identifying and predicting security anomalies in operating systems using graph neural networks. 4. Development of a software layout and evaluation of its effectiveness. During the work, anomalies and methods for their prediction were analyzed and systematized, graph neural networks were analyzed, and a software model of methods for identifying and predicting anomalies using graph neural networks was implemented. The work resulted a software model for identifying and predicting anomalies was developed and its effectiveness was assessed. The results could be used as basis for further modifications of forecasting and anomaly detection methods.