{"title":"DDOS ATTACK DETECTION IN TELECOMMUNICATION NETWORK\nUSING MACHINE LEARNING","authors":"A Pasumponpandian, S. Smys","doi":"10.36548/jucct.2019.1.004","DOIUrl":null,"url":null,"abstract":"The telecommunication network that is the assemblage of the terminal nodes enables the whole to be connected. The swift progress in the telecommunication networks and the information technology has enabled a seamless connection and the capacity to store and communicate vast scale of information in the form of text and voice that are sensitive. This makes the telecommunication networks prey to multiple cyber-threats of which the DDOS (distributed denial of service) are the more predominant type of the cyber-threat causing the denial of the services to the users. So the paper utilizing the combination of the neural network and the support vector machine presents the detection and the classification method for the DDOS attacks in the telecommunication network. The performance evaluation using the network simulator-2 enables to have the enhanced detection accuracy for the proposed method.","PeriodicalId":443052,"journal":{"name":"Journal of Ubiquitous Computing and Communication Technologies","volume":"6 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-09-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"49","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Ubiquitous Computing and Communication Technologies","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.36548/jucct.2019.1.004","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 49
Abstract
The telecommunication network that is the assemblage of the terminal nodes enables the whole to be connected. The swift progress in the telecommunication networks and the information technology has enabled a seamless connection and the capacity to store and communicate vast scale of information in the form of text and voice that are sensitive. This makes the telecommunication networks prey to multiple cyber-threats of which the DDOS (distributed denial of service) are the more predominant type of the cyber-threat causing the denial of the services to the users. So the paper utilizing the combination of the neural network and the support vector machine presents the detection and the classification method for the DDOS attacks in the telecommunication network. The performance evaluation using the network simulator-2 enables to have the enhanced detection accuracy for the proposed method.