Enhancing Cyber-Resilience of Automatic Generation Control through Moving Target Defense Conference

Islam, S, Haider, MZ, Sun, M et al. (2026). Enhancing Cyber-Resilience of Automatic Generation Control through Moving Target Defense . 2017 IEEE POWER & ENERGY SOCIETY GENERAL MEETING, 10.1109/PESGM58988.2026.11693188

cited authors

  • Islam, S; Haider, MZ; Sun, M; Rahman, MA

authors

abstract

  • False data injection (FDI) attacks on automatic generation control (AGC) infrastructures covertly manipulate frequency measurements, which can mislead the control loop and disrupt the system's normal operation. The falsified measurements propagate through power system dynamics, causing inter-area power oscillations, rotor angle divergence, frequency oscillations, and voltage instability. In this paper, we demonstrate that the moving target defense (MTD) strategy offers superior capability in detecting stealthy FDI attacks in state estimation compared to systems operating without MTD under similar attack conditions. To achieve this, this paper presents a unified cyber-physical framework that integrates the IEEE-39 bus system with a linearized AC state estimation-based bad data detection (BDD) technique and MTD in reference power setpoint. Traditional BDD can not accurately detect stealthy FDI attacks because the attacker knows the system dynamics and will carefully inject corrupted data that mimics system measurements. However, the attacker's lack of awareness of the controlled MTD in specific generators increases the model-measurement inconsistency and enhances the probability of attack detection, which is 32.7% in this study. MTD in reference power setpoint as controlled randomization provides a proactive defense mechanism against stealthy attacks applied to certain measurements.

publication date

  • January 1, 2026

published in

Digital Object Identifier (DOI)