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An overview of neural networks use in anomaly Intrusion Detection Systems

机译:神经网络在异常入侵检测系统中的应用概述

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With the increasing number of computers being connected to the Internet, security of an information system has never been more urgent. Because no system can be absolutely secure, the timely and accurate detection of intrusions is necessary. This is the reason of an entire area of research, called Intrusion Detection Systems (IDS). Anomaly systems detect intrusions by searching for an abnormal system activity. But the main problem of anomaly detection IDS is that; it is very difficult to build, because of the difficulty in defining what is normal and what is abnormal. Neural network with its ability of learning has become one of the most promising techniques to solve this problem. This paper presents an overview of neural networks and their use in building anomaly intrusion systems.
机译:随着越来越多的计算机连接到Internet,信息系统的安全从未像现在这样迫切。由于没有绝对安全的系统,因此必须及时准确地检测到入侵。这是整个研究领域的原因,被称为入侵检测系统(IDS)。异常系统通过搜索异常系统活动来检测入侵。但是,异常检测IDS的主要问题是:由于很难定义正常和异常,因此很难构建。具有学习能力的神经网络已成为解决该问题的最有前途的技术之一。本文概述了神经网络及其在构建异常入侵系统中的用途。

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