Sharma, Mridula2020-04-082020-04-0820202020-04-08http://hdl.handle.net/1828/11675The 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.enAvailable to the World Wide WebCPSSupervised Machine LearningRPLFeature SelectionEvaluating and enhancing the security of cyber physical systems using machine learning approachesThesisM. 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. 1145–1151M. 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.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)M. Sharma, F. Gebali, H. Elmiligi, A. Sharma, "Simulating Attacks for RPL and Generating Multi-class Dataset for Supervised Machine Learning", IEMCON 2019M. 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)