2019/03/19 by Zhigang Chu, Jiazi Zhang, Chu, Zhigang +5 · 1 citation
Computer Science · Engineering · #FOS: Electrical engineering #Information and Cyber Security #Network Security and Intrusion Detection #Smart Grid Security and Resilience #Systems and Control (eess.SY) #cs.SY #eess.SY #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.1903.07781
8 pages, 5 figures, 1 table. arXiv admin note: text overlap with arXiv:1705.04218
arxiv created 2019/03/19 · openalex publication_date 2019/03/19 · arxiv updated 2020/11/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper studies the vulnerability of large-scale power systems to false data injection (FDI) attacks through their physical consequences. Prior work has shown that an attacker-defender bi-level linear program (ADBLP) can be used to determine the worst-case consequences of FDI attacks aiming to maximize the physical power flow on a target line. Understanding the consequences of these attacks requires consideration of power system operations commonly used in practice, specifically real-time contingency analysis (RTCA) and security constrained economic dispatch (SCED). An ADBLP is formulated with detailed assumptions on attacker's knowledge, and a modified Benders' decomposition algorithm is introduced to solve such an ADBLP. The vulnerability analysis results presented for the synthetic Texas system with 2000 buses show that intelligent FDI attacks can cause post-contingency overflows.