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Machine Learning Model of an Intelligent Decision Support System in the Information Security Sphere

机译:信息安全领域智能决策支持系统的机器学习模型

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摘要

The article defines an approach to solving the task of network traffic analysis in higher education establishments (HEE) with the aim of detecting information security threats (IST) to systems, services, and networks. The approach implies using a machine learning model which utilizes neural network technology to classify running network activity as normal or abnormal, the two predetermined classes. In order to determine initial data for teaching and testing the machine learning model a specific approach was designed. The approach implies determination of a local network element, installation of necessary software, network analysis under the circumstances of normal network activity, network analysis under the circumstances of abnormal network activity, data processing and formation of a representative teaching selection.
机译:本文定义了一种解决高等教育机构(HEE)中网络流量分析任务的方法,旨在检测对系统,服务和网络的信息安全威胁(IST)。该方法意味着使用机器学习模型,该模型利用神经网络技术将运行中的网络活动分类为正常或异常(两个预定类别)。为了确定用于教学和测试机器学习模型的初始数据,设计了一种特定的方法。该方法意味着确定本地网络元素,安装必要的软件,在正常网络活动情况下进行网络分析,在异常网络活动情况下进行网络分析,数据处理以及形成具有代表性的教学选择。

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