Online False Data Injection Attack Detection With Wavelet Transform and Deep Neural Networks

By James Jian Qiao Yu, Yunhe Hou, Victor O. K. Li. IEEE Transactions on Industrial Informatics, 2018

311 citations recorded by the source corpus.

State estimation is critical to the operation and control of modern power systems. However, many cyber-attacks, such as false data injection attacks, can circumvent conventional detection methods and interfere the normal operation of grids. While there exists research focusing on detecting such attacks in dc state estimation, attack detection in ac systems is also critical, since ac state estimation is more widely employed in power utilities. In this paper, we propose a new false data injection attack detection mechanism for ac state estimation. When malicious data are injected in the state vectors, their spatial and temporal data correlations may deviate from those in normal operating conditions. The proposed mechanism can effectively capture such inconsistency by analyzing temporally consecutive estimated system states using wavelet transform and deep neural network techniques. We assess the performance of the proposed mechanism with comprehensive case studies on IEEE 118- and 300-bus power systems. The results indicate that the mechanism can achieve a satisfactory attack detection accuracy. Furthermore, we conduct a preliminary sensitivity test on the control parameters of the proposed mechanism.

Subfields: Artificial Intelligence, Computer Networks and Communications, Control and Systems Engineering

View Paper: https://www.semanticscholar.org/paper/bf599a6863c524dda9a1b6dbc5ecbb2e31e556a4

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Computer Networks and Communications

1. Mohammad Shahidehpour
2. Yuanzheng Li
3. Zhaoyang Dong
4. Xinhao Wei

In Control and Systems Engineering

1. Mohammad Shahidehpour
2. Yuanzheng Li
3. Zhaoyang Dong
4. Xinhao Wei
5. Fahad Alismail

Citations in the corpus

• Detection of False Data Injection Attacks in Smart Grid: A Secure Federated Deep Learning Approach (2022, methodology): “[19] use GRU and wavelet transform to detect FDIA in power system.”