Date of Award
1-1-2022
Publication Type
Thesis
Degree Name
M.A.Sc.
Department
Electrical and Computer Engineering
Keywords
Water storage, Dimensionality reduction, Intrusion detection
Supervisor
J. Ahamed
Supervisor
B. Rashidzadeh
Rights
info:eu-repo/semantics/openAccess
Abstract
Supervisory control and data acquisition (SCADA) systems are often imperiled bycyber-attacks, which can often be detected using intrusion detection system (IDSs).However, the performance and efficiency of IDSs can be affected by several factors,including the quality of data, curse of dimensionality of the data, and computationalcost. Feature reduction techniques can overcome most of these challenges by eliminatingthe redundant and non-informative features, thereby increasing the detectionaccuracy. This study aims to shows the importance of feature reduction on the intrusiondetection performance. To do this, a multi-modular IDS is designed that isconnected to the SCADA system of a water storage tank. A comparative study isalso performed by employing advanced feature selection and dimensionality reductiontechniques. The utilized feature reduction techniques improves the IDS efficiency byreducing the memory usage and using data with better quality, which in turn increasethe detection accuracy. The obtained results have been analyzed in terms of F1-scoreand accuracy.
Recommended Citation
Aljoudi, Ranim, "A Critical Study on the Effect of Dimensionality Reduction on Intrusion Detection in Water Storage Critical Infrastructure" (2022). Electronic Theses and Dissertations. 8701.
https://scholar.uwindsor.ca/etd/8701