{"title":"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","authors":"D. Parfenov, I. Bolodurina","doi":"10.1109/TSP.2018.8441435","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":383018,"journal":{"name":"2018 41st International Conference on Telecommunications and Signal Processing (TSP)","volume":"125 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Investigation of the Neural Network Model for Security and Quality of Service for a Multi-Cloud System in Virtual Data Center\",\"authors\":\"D. Parfenov, I. Bolodurina\",\"doi\":\"10.1109/TSP.2018.8441435\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":383018,\"journal\":{\"name\":\"2018 41st International Conference on Telecommunications and Signal Processing (TSP)\",\"volume\":\"125 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 41st International Conference on Telecommunications and Signal Processing (TSP)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/TSP.2018.8441435\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 41st International Conference on Telecommunications and Signal Processing (TSP)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/TSP.2018.8441435","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
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.