Toggle Main Menu Toggle Search

Open Access padlockePrints

A Stealthier False Data Injection Attack against the Power Grid

Lookup NU author(s): Dr Muhammad Ramadan SaifuddinORCiD


Full text for this publication is not currently held within this repository. Alternative links are provided below where available.


We use discrete-time adaptive control theory to design a novel false data injection (FDI) attack against automatic generation control (AGC), a critical system that maintains a power grid at its requisite frequency. FDI attacks can cause equipment damage or blackouts by falsifying measurements in the streaming sensor data used to monitor the grid's operation. Compared to prior work, the proposed attack (i) requires less knowledge on the part of the attacker, such as correctly forecasting the future demand for power; (ii) is stealthier in its ability to bypass standard methods for detecting bad sensor data and to keep the false sensor readings near historical norms until the attack is well underway; and (iii) can sustain the frequency excursion as long as needed to cause real-world damage, in spite of AGC countermeasures. We validate the performance of the proposed attack on realistic 37-bus and 118-bus setups in PowerWorld, an industry-strength power system simulator trusted by real-world operators. The results demonstrate the attack's improved stealthiness and effectiveness compared to prior work.

Publication metadata

Author(s): Yan W, Lou X, Yau D, Yang Y, Saifuddin R, Wu J, Winslett M

Publication type: Conference Proceedings (inc. Abstract)

Publication status: Published

Conference Name: 2021 IEEE International Conference on Communications, Control, and Computing Technologies for Smart Grids (SmartGridComm)

Year of Conference: 2021

Pages: 108-114

Print publication date: 13/12/2021

Online publication date: 13/12/2021

Acceptance date: 13/12/2021

Publisher: IEEE


DOI: 10.1109/SmartGridComm51999.2021.9632337

Library holdings: Search Newcastle University Library for this item

ISBN: 9781665415026