Marcio Andrey Teixeira, Maede Zolanvari, Khaled M. Khan, Raj Jain, Nader Meskin
{"title":"监控和数据采集系统中基于流的入侵检测算法:一种实时方法","authors":"Marcio Andrey Teixeira, Maede Zolanvari, Khaled M. Khan, Raj Jain, Nader Meskin","doi":"10.1049/cps2.12016","DOIUrl":null,"url":null,"abstract":"<p>Intrusion detection in supervisory control and data acquisition (SCADA) systems is integral because of the critical roles of these systems in industries. However, available approaches in the literature lack representative flow-based datasets and reliable real-time adaption and evaluation. A publicly available labelled dataset to support flow-based intrusion detection research specific to SCADA systems is presented. Cyberattacks were carried out against our SCADA system test bed to generate this flow-based dataset. Moreover, a flow-based intrusion detection system (IDS) is developed for SCADA systems using a deep learning algorithm. We used the dataset to develop this IDS model for real-time operations of SCADA systems to detect attacks momentarily after they happen. The results show empirical proof of the model’s adequacy when deployed online to detect cyberattacks in real time.</p>","PeriodicalId":36881,"journal":{"name":"IET Cyber-Physical Systems: Theory and Applications","volume":"6 3","pages":"178-191"},"PeriodicalIF":1.7000,"publicationDate":"2021-05-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/cps2.12016","citationCount":"4","resultStr":"{\"title\":\"Flow-based intrusion detection algorithm for supervisory control and data acquisition systems: A real-time approach\",\"authors\":\"Marcio Andrey Teixeira, Maede Zolanvari, Khaled M. Khan, Raj Jain, Nader Meskin\",\"doi\":\"10.1049/cps2.12016\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>Intrusion detection in supervisory control and data acquisition (SCADA) systems is integral because of the critical roles of these systems in industries. However, available approaches in the literature lack representative flow-based datasets and reliable real-time adaption and evaluation. A publicly available labelled dataset to support flow-based intrusion detection research specific to SCADA systems is presented. Cyberattacks were carried out against our SCADA system test bed to generate this flow-based dataset. Moreover, a flow-based intrusion detection system (IDS) is developed for SCADA systems using a deep learning algorithm. We used the dataset to develop this IDS model for real-time operations of SCADA systems to detect attacks momentarily after they happen. The results show empirical proof of the model’s adequacy when deployed online to detect cyberattacks in real time.</p>\",\"PeriodicalId\":36881,\"journal\":{\"name\":\"IET Cyber-Physical Systems: Theory and Applications\",\"volume\":\"6 3\",\"pages\":\"178-191\"},\"PeriodicalIF\":1.7000,\"publicationDate\":\"2021-05-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ietresearch.onlinelibrary.wiley.com/doi/epdf/10.1049/cps2.12016\",\"citationCount\":\"4\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IET Cyber-Physical Systems: Theory and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1049/cps2.12016\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q3\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IET Cyber-Physical Systems: Theory and Applications","FirstCategoryId":"1085","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1049/cps2.12016","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Flow-based intrusion detection algorithm for supervisory control and data acquisition systems: A real-time approach
Intrusion detection in supervisory control and data acquisition (SCADA) systems is integral because of the critical roles of these systems in industries. However, available approaches in the literature lack representative flow-based datasets and reliable real-time adaption and evaluation. A publicly available labelled dataset to support flow-based intrusion detection research specific to SCADA systems is presented. Cyberattacks were carried out against our SCADA system test bed to generate this flow-based dataset. Moreover, a flow-based intrusion detection system (IDS) is developed for SCADA systems using a deep learning algorithm. We used the dataset to develop this IDS model for real-time operations of SCADA systems to detect attacks momentarily after they happen. The results show empirical proof of the model’s adequacy when deployed online to detect cyberattacks in real time.