{"title":"Cyber attack and defense on industry control systems","authors":"Chih-Ta Lin, Sung-Lin Wu, Mei-Lin Lee","doi":"10.1109/DESEC.2017.8073874","DOIUrl":null,"url":null,"abstract":"Industry control systems (ICSs) are widely used in various critical infrastructure production facilities of the oil, water, and electricity industries. In the past, most of these ICSs lacked both authentication and encryption mechanisms, leaving them vulnerable to attack by hackers. By establishing an industry control system test bed, this paper examines two operational cases, viz. water level control and air pollution control, and develops for them a Modbus/TCP network attack program, and an associated intrusion detection system (IDS). Through in-depth analysis of the Modbus ICS protocol, an automatic-learning based method of malicious intrusion detection is proposed, with which a variety of tests are conducted on the developed testbed. The results show that this method can effectively detect various kinds of network attacks.","PeriodicalId":92346,"journal":{"name":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","volume":"530 1","pages":"524-526"},"PeriodicalIF":0.0000,"publicationDate":"2017-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"38","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"DASC-PICom-DataCom-CyberSciTech 2017 : 2017 IEEE 15th International Conference on Dependable, Autonomic and Secure Computing ; 2017 IEEE 15th International Conference on Pervasive Intelligence and Computing ; 2017 IEEE 3rd International...","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/DESEC.2017.8073874","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 38
Abstract
Industry control systems (ICSs) are widely used in various critical infrastructure production facilities of the oil, water, and electricity industries. In the past, most of these ICSs lacked both authentication and encryption mechanisms, leaving them vulnerable to attack by hackers. By establishing an industry control system test bed, this paper examines two operational cases, viz. water level control and air pollution control, and develops for them a Modbus/TCP network attack program, and an associated intrusion detection system (IDS). Through in-depth analysis of the Modbus ICS protocol, an automatic-learning based method of malicious intrusion detection is proposed, with which a variety of tests are conducted on the developed testbed. The results show that this method can effectively detect various kinds of network attacks.