IEC-61850 Protocol Analysis and Online Intrusion Detection System for SCADA Networks using Machine Learning
| dc.contributor.author | Patel, Shivam | |
| dc.contributor.supervisor | Dong, Xiaodai | |
| dc.date.accessioned | 2018-05-07T17:47:31Z | |
| dc.date.available | 2018-05-07T17:47:31Z | |
| dc.date.copyright | 2017 | en_US |
| dc.date.issued | 2018-05-07 | |
| dc.degree.department | Department of Electrical and Computer Engineering | en_US |
| dc.degree.level | Master of Engineering M.Eng. | en_US |
| dc.description.abstract | Nowadays, industrial network security has become a major threat. In order to detect and prevent any type of attack on the industrial networks it is necessary to understand the communication protocols used by them. Hence, the first part of the report would review research done on IEC (International Electro Technical Commission) -61850 protocol employed in electric substation environment. In the second part of the project, an online intrusion detection system (OIDS) for SCADA networks which uses machine learning for detection is implemented. OIDS is a testbed which emulates a typical SCADA network and it consists of both attack and defense toolkits. SNORT is used for detecting the attack traffic based on the machine learning weights. The machine learning weights are obtained by training the collected traffic using the logistic regression algorithm. | en_US |
| dc.description.scholarlevel | Graduate | en_US |
| dc.identifier.uri | http://hdl.handle.net/1828/9347 | |
| dc.language.iso | en | en_US |
| dc.rights | Available to the World Wide Web | en_US |
| dc.subject | Report | en_US |
| dc.title | IEC-61850 Protocol Analysis and Online Intrusion Detection System for SCADA Networks using Machine Learning | en_US |
| dc.type | project | en_US |