Date of Award

5-2025

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Degree Discipline

Education Leadership

Abstract

The Smart Grid is an improvement on the conventional grid that uses advanced communication methods and new technology for the production, transmission, and distribution of electrical power. The modern Smart Grid 's ability to function successfully depends heavily on its communication infrastructure. Today, the usage of communication technology promotes energy efficiency, coordination amongst all Smart Grid components, from generation to end users, and optimal Smart Grid functioning. The communication network of the Smart Grid exchanges data regarding the condition of its numerous integrated IEDs (intelligent electronic devices); however, there are always chances for attackers to interrupt utility resources, interfere with communication networks, or steal customers' intellectual property and private information due to the different amounts of IEDs connected across Smart Grid Communication Networks.

Additionally, as Distributed Energy Resources (DER) and dynamic loads become more prevalent, phase angle values that are crucial for Phasor Measurement Units (PMUs) change, and real-time control has emerged as a key tool for tracking power system performance in today's Smart Grid technology. Because of their link to the Smart Grid 's communication network, Phasor Measurement Units devices are now susceptible to cyberattacks. Because of the recent global security incidents and new cyberthreats, this development has created new cyber-security issues for the Smart Grid and is a very worrying issue.

The effects of Distributed Denial of Service (DDOS) assaults on PMU data transfers over Smart Grid communication networks in the form of NetFlows were carefully examined in this study. For the first time in the literature, a combination of the Secure Network Analytics (SNA) tool, Intrusion Detection System, and firewall were used to model the DDOS attack in the Smart Grid 's communication network. Additionally, risk reduction and good security hygiene are enhanced by employing the Secure Network Analytics (SNA) tool to establish a security baseline for the Smart Grid system.

The research findings are in contrast with those found in previous studies. Our findings demonstrated that this research strategy outperformed previous approaches in the literature in terms of mitigating and detecting DDOS attacks.

Index Terms: Detection and mitigation, distributed denial of service (DDOS) attack, distributed energy resources, firewall, intrusion detection and prevention systems, phase measurement units, Smart Grid system.

Committee Chair/Advisor

Penrose Cofie

Committee Member

Cajetan M. Akujuobi

Committee Member

John Fuller

Committee Member

Emmanuel Dada

Committee Member

Annamalai Annamalai

Publisher

Prairie View A&M University

Rights

© 2021 Prairie View A & M University

Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.

Date of Digitization

4/29/2025

Contributing Institution

J. B . Coleman Library

City of Publication

Prairie View

MIME Type

Application/PDF

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