虚拟数据中心多云系统安全与服务质量的神经网络模型研究

D. Parfenov, I. Bolodurina
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引用次数: 0

摘要

在本研究中,开发和研究了一个自治系统的原型,以提供多云平台的网络安全和服务质量。在此基础上建立了交通分析的数学模型。数学模型是基于神经网络的。设计了一种基于多层感知器和自组织Kohonen网络的混合神经网络。这种方法允许更准确地分类和检测恶意流量。实验研究表明,采用该方法可以提高对拒绝服务等攻击的检测效率。同时,在攻击过程中,在多云平台网络中保持所需的服务质量。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Investigation of the Neural Network Model for Security and Quality of Service for a Multi-Cloud System in Virtual Data Center
In this study, a prototype of an autonomous system was developed and investigated to provide cyber security and quality of service for multi-cloud platforms. Based on the developed system is a mathematical model of traffic analysis. The mathematical model is based on the neural network. A hybrid neural network based on a multi-layer perceptron and a self-organizing Kohonen network was designed. This approach allowed to more accurately classify and detect malicious traffic. The conducted experimental researches have shown that using the proposed approach allows to increase the effectiveness of detection of such attacks as denial of service. At the same time, during the attack, the required quality of service is maintained in the multi-cloud platform network.
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