Evaluating and enhancing the security of cyber physical systems using machine learning approaches
| dc.contributor.author | Sharma, Mridula | |
| dc.contributor.supervisor | Gebali, Fayez | |
| dc.contributor.supervisor | Elmiligi, Haytham | |
| dc.date.accessioned | 2020-04-08T20:35:55Z | |
| dc.date.available | 2020-04-08T20:35:55Z | |
| dc.date.copyright | 2020 | en_US |
| dc.date.issued | 2020-04-08 | |
| dc.degree.department | Department of Electrical and Computer Engineering | en_US |
| dc.degree.level | Doctor of Philosophy Ph.D. | en_US |
| dc.description.abstract | The main aim of this dissertation is to address the security issues of the physical layer of Cyber Physical Systems. The network security is first assessed using a 5-level Network Security Evaluation Scheme (NSES). The network security is then enhanced using a novel Intrusion Detection System that is designed using Supervised Machine Learning. Defined as a complete architecture, this framework includes a complete packet analysis of radio traffic of Routing Protocol for Low-Power and Lossy Networks (RPL). A dataset of 300 different simulations of RPL network is defined for normal traffic, hello flood attack, DIS attack, increased version attack and decreased rank attack. The IDS is a multi-model detection model that provides an efficient detection against the known as well as new attacks. The model analysis is done with the cross-validation method as well as using the new data from a similar network. To detect the known attacks, the model performed at 99% accuracy rate and for the new attack, 85% accuracy is achieved. | en_US |
| dc.description.scholarlevel | Graduate | en_US |
| dc.identifier.bibliographicCitation | M. Sharma, F. Gebali, H. Elmiligi, and M. Rahman, “Network security evalua-tion scheme for wsn in cyber-physical systems,” in2018 IEEE 9th Annual Infor-mation Technology, Electronics and Mobile Communication Conference (IEM-CON), Nov 2018, pp. 1145–1151 | en_US |
| dc.identifier.bibliographicCitation | M. Sharma, F. Gebali, and H. Elmiligi, “3-dimensional analysis of cyber-physicalsystems attacks,” in2018 4th International Conference on Computing Communication and Automation (ICCCA), Dec 2018, pp. 1–5. | en_US |
| dc.identifier.bibliographicCitation | M. Sharma, H. Elmiligi, F. Gebali, "Network Security and Privacy Evaluation Scheme for Cyber Physical Systems (CPS)" in "Security of Cyber-Physical System: Vulnerability and Impact", springer (Accepted) | en_US |
| dc.identifier.bibliographicCitation | M. Sharma, F. Gebali, H. Elmiligi, A. Sharma, "Simulating Attacks for RPL and Generating Multi-class Dataset for Supervised Machine Learning", IEMCON 2019 | en_US |
| dc.identifier.bibliographicCitation | M. Sharma, H. Elmiligi, F. Gebali, "A Novel Intrusion Detection System for detecting RPL attacks in Cyber Physical Systems", IEEE Access(Final submission after minor edits) | en_US |
| dc.identifier.uri | http://hdl.handle.net/1828/11675 | |
| dc.language | English | eng |
| dc.language.iso | en | en_US |
| dc.rights | Available to the World Wide Web | en_US |
| dc.subject | CPS | en_US |
| dc.subject | Supervised Machine Learning | en_US |
| dc.subject | RPL | en_US |
| dc.subject | Feature Selection | en_US |
| dc.title | Evaluating and enhancing the security of cyber physical systems using machine learning approaches | en_US |
| dc.type | Thesis | en_US |