Abstract-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 attackerdefender 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 realtime 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. Index Terms-False data injection attack, cyber-security, vulnerability of N − 1 reliable power system, bi-level optimization.
Chu at el. studied the vulnerability of power system by targeting a specific line when another line trips REF .
Vulnerability Assessment of N-1 Reliable Power Systems to False Data Injection Attacks
ArXiv
ArXiv
Computer Science Mathematics