A novel detection and defense mechanism against false data injection attack in smart grids

As the next generation of green power system, smart grids have gradually enhanced operation efficiency system. Meanwhile, application communication and intelligent technologies make grid more vulnerable to emerging cyber-physical attacks, such as false data injection attack (FDIA). Particularly, deception property FDIA on output measurement estimation can fool current security mechanism without triggering an alarm. Motivated by this problem, paper aims at developing a novel detection recovery against in grid. Based established state space model derived from three-phase sinusoidal voltage equations, improved principal component analysis (PCA)-based method is proposed. By introducing mathematical transformation principle method, performance rate positive be improved. To keep stable running genetic optimization algorithm-based linear quadratic regulator (LQR) defense developed. In addition, improve response external artificial intelligence named algorithm introduced optimize robust proposed method. Finally, simulation results IEEE 6-bus 118-bus system demonstrate superiority optimization-based LQR