Power Grid AC-based State Estimation: Vulnerability Analysis Against Cyber Attacks

We analyze the vulnerability of AC-based power system state estimation (SE) to false data injection attacks (FDIA). A convexification framework based on semidefinite programming (SDP) solves the FDIA design efficiently despite nonlinear AC models and sparsity constraints. From optimal SDP solutions, we delineate attackable regions given measurement types and grid topology, prove stealthiness and sparsity properties, and derive performance bounds. Simulations on IEEE test cases validate the approach and inform protection via security metrics, redesigned bad data detection, and grid hardening.