Afaf D. Althobiti, Rabab M. Almohayawi, O. Bamasag
{"title":"安全软件定义网络的机器学习方法:机器学习和人工智能","authors":"Afaf D. Althobiti, Rabab M. Almohayawi, O. Bamasag","doi":"10.1145/3440749.3442597","DOIUrl":null,"url":null,"abstract":"This paper proposes network security enhancement solution aiming to improving the level of performance in the detection of cyber-attacks on Software Defined Network (SDN) it will prevent against Denial of Service Attack. We are going to employ two solution and comparing on the SDN attack detection performance. The first approach is the performance accuracy of the SDN with IDS procedural, and the second approach is the integration of SDN with Machine Learning. The project serves the organization generally in the field of information security, network security and cybersecurity awareness. The system performance evaluation results prove the system is capable to provide the effective DDoS attack detection and provide security enhancement in Software Defined Network.","PeriodicalId":344578,"journal":{"name":"Proceedings of the 4th International Conference on Future Networks and Distributed Systems","volume":"43 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2020-11-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Machine Learning approach to Secure Software Defined Network: Machine Learning and Artificial Intelligence\",\"authors\":\"Afaf D. Althobiti, Rabab M. Almohayawi, O. Bamasag\",\"doi\":\"10.1145/3440749.3442597\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper proposes network security enhancement solution aiming to improving the level of performance in the detection of cyber-attacks on Software Defined Network (SDN) it will prevent against Denial of Service Attack. We are going to employ two solution and comparing on the SDN attack detection performance. The first approach is the performance accuracy of the SDN with IDS procedural, and the second approach is the integration of SDN with Machine Learning. The project serves the organization generally in the field of information security, network security and cybersecurity awareness. The system performance evaluation results prove the system is capable to provide the effective DDoS attack detection and provide security enhancement in Software Defined Network.\",\"PeriodicalId\":344578,\"journal\":{\"name\":\"Proceedings of the 4th International Conference on Future Networks and Distributed Systems\",\"volume\":\"43 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2020-11-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the 4th International Conference on Future Networks and Distributed Systems\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1145/3440749.3442597\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the 4th International Conference on Future Networks and Distributed Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3440749.3442597","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Machine Learning approach to Secure Software Defined Network: Machine Learning and Artificial Intelligence
This paper proposes network security enhancement solution aiming to improving the level of performance in the detection of cyber-attacks on Software Defined Network (SDN) it will prevent against Denial of Service Attack. We are going to employ two solution and comparing on the SDN attack detection performance. The first approach is the performance accuracy of the SDN with IDS procedural, and the second approach is the integration of SDN with Machine Learning. The project serves the organization generally in the field of information security, network security and cybersecurity awareness. The system performance evaluation results prove the system is capable to provide the effective DDoS attack detection and provide security enhancement in Software Defined Network.