Abstract

Smart grid technologies are integral to society’s transition to sustainable energy sources, but they do not come without a cost. As the energy sector shifts away from a century’s reliance on fossil fuels and centralized generation, technology that actively monitors and controls every aspect of the power infrastructure has been widely adopted, resulting in a plethora of new vulnerabilities that have already wreaked havoc on critical infrastructure. Integrity attacks that feedback false data through industrial control systems, which result in possible catastrophic overcorrections and ensuing failures, have plagued grid infrastructure over the past several years. This threat is now at an all-time high and shows little sign of cooling off.

To combat this trajectory, this research explores the potential for simulated grid characteristics to examine robust security measures by use of a cyber-physical system (CPS) testbed constructed across the University of Central Florida (UCF) Resilient, Intelligent and Sustainable Energy Systems (RISES) Lab Cluster. This thesis explores hypothesized defense mechanisms and awareness algorithms to protect against unforeseen vulnerabilities brought on by grid attacks that will test the boundaries of commercial cybersecurity standards. Through an extensive probe across proposed defenses and vulnerability analysis of industrial systems, a blueprint for future research is outlined that will yield results that have the potential to ripple improvements across the power sector. The sanctity of critical infrastructure is of the highest priority for global powers. As such, this research bolsters the tools at the disposal of international entities and seeks to protect the ever-expanding lifestyle that reliable access to energy provides.

Thesis Completion

2022

Semester

Spring

Thesis Chair/Advisor

Qu, Zhihua

Degree

Bachelor of Arts (B.A.)

College

College of Engineering and Computer Science

Department

Electrical and Computer Engineering

Degree Program

Electrical Engineering

Language

English

Access Status

Open Access

Release Date

5-1-2022

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