False Data Injection Attacks and detection scenarios in the power system

False Data Injection Attacks (FDIA) in smart grid is an object of extensive investigation. Attack strategies and detection methodologies have been proposed by various researchers. The aim of the attacker is to bias the state estimate. This paper proposes to calculate a figure of merit of the bias in the state variables introduced by the attacker, known as Aberration Index. Normalised residues indicate the effect of the attacks on the measurements. This paper discusses the detection of attacks using Aberration Index and Normalised residues for different attack scenarios.