Date of Graduation
12-2025
Document Type
Thesis
Degree Name
Master of Science in Computer Science (MS)
Degree Level
Graduate
Department
Computer Science & Computer Engineering
Advisor/Mentor
Li, Qinghua
Committee Member
Jin, Kevin
Second Committee Member
Pan, Yanjun
Keywords
Cyber-Physical Co-Simulation; Distributed Energy Resources (DER); Hybrid Approach for Mitigation; Vulnerability-Based Cyber Threat Modeling
Abstract
Distributed Energy Resources including small-scale generation, storage, and controllable loads are increasingly integral to modern distribution systems. While compromises of individual devices may appear localized, coordinated exploitation at scale can threaten grid stability. This thesis investigates large-scale cyber attacks on Distributed Energy Resources (DER) and develops a tractable, vulnerability-driven framework to model, analyze, and mitigate their risks. We propose a graph-based cyber threat model based on DER network topologies and vulnerabilities on devices, and design an efficient search algorithm to identify high-risk attack scenarios from the exponentially large attack space. These attack scenarios are evaluated through a cyber-physical co-simulation environment that quantifies their operational impact on the power grid using voltage deviation metrics. To support remediation decisions, we introduce a hybrid vulnerability prioritization framework that combines path-based risk contribution with social network-based centrality metrics, producing composite scores that categorize vulnerabilities into actionable priority levels. This scheme has practical applications for grid operators and security engineers, providing a means to understand when DER-side attacks become operationally significant, identify which vulnerabilities most elevate system risk, and allocate limited remediation resources effectively. We present experimental evaluations demonstrating the effectiveness of our search strategies and the validity of our prioritization approach across representative DER network configurations.
Citation
Neaz, F. (2025). Cyber Threat Modeling, Risk Analysis, and Mitigation for Power Grids with Distributed Energy Resources. Graduate Theses and Dissertations Retrieved from https://scholarworks.uark.edu/etd/6069
