Efficient detection of false data injection attacks on AC state estimation in smart grids

Abstract

This paper proposes a simple non-iterative technique for detecting false data injection attacks on alternating current (AC) state estimators. The proposed method uses the nodal power injections and line power flows from the supervisory control and data acquisition (SCADA) system and voltage magnitudes and angles from phasor measurement units (PMUs) to the detect the false data injection attack. As the proposed method is independent of the state estimation outputs and does not depend on any other energy management system (EMS) functionality, it can be used to test the quality of the data even before the execution of the state estimation algorithm. The proposed method has been tested in the IEEE 118 bus system where false data with a magnitude ranging from 1% to 10 % is injected in four pairs of line power flows and one voltage measurement. It has been demonstrated that the proposed method can detect such attacks even when the attack magnitude is as small as 1%, which is not able to be deducted by conventional bad data detection techniques.