On Stealthiness and Effectiveness of Moving Target Defense in Smart Grids

Recent studies have proposed moving target defense (MTD) to detect false data injection (FDI) attacks in power grids. To hide the activation of MTD from attackers, a hidden MTD (HMTD) has been proposed, which keeps the system power flow after MTD unchanged. It has been proved that HMTD cannot detect all FDI attacks because of its stealthiness requirements. However, the mathematical mechanism of MTD's stealthiness has yet to be revealed. The maximum detection capability of HMTD is also unclear. To address the abovementioned issues, we first analyze the maximum detection capability of HMTD based on graph theory and propose the topological condition to achieve it. Moreover, we study the essential characteristics of HMTD and find that all HMTD schemes are in a space spanned by branch parameters. We further propose a multistage HMTD (MHMTD) method to select multiple HMTD schemes in this space to maximize the detection capability. Experiments show that the MHMTD can maximize the detection capability of HMTD in all test systems with high stealthy probability.

Authors

Institutions

Publication Details

Journal
IEEE Transactions on Industrial Informatics
Published
2025-01-27
DOI
https://doi.org/10.1109/tii.2024.3514211
Citations
3
Primary Topic
Smart Grid and Power Systems
Type
article
Field-Weighted Citation Impact
2.19

Funders

Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

On Stealthiness and Effectiveness of Moving Target Defense in Smart Grids

Gaoxi Xiao, Jiazhou Wang, Hao Huang, Yadong Zhou et al.
3 citations
IEEE Transactions on Industrial Informatics
Smart Grid and Power Systems
2.19
article

On Stealthiness and Effectiveness of Moving Target Defense in Smart Grids

Gaoxi Xiao, Jiazhou Wang, Hao Huang, Yadong Zhou, Jue Tian, Ting Liu, Yang Liu
article en
3 citations

Abstract

Recent studies have proposed moving target defense (MTD) to detect false data injection (FDI) attacks in power grids. To hide the activation of MTD from attackers, a hidden MTD (HMTD) has been proposed, which keeps the system power flow after MTD unchanged. It has been proved that HMTD cannot detect all FDI attacks because of its stealthiness requirements. However, the mathematical mechanism of MTD's stealthiness has yet to be revealed. The maximum detection capability of HMTD is also unclear. To address the abovementioned issues, we first analyze the maximum detection capability of HMTD based on graph theory and propose the topological condition to achieve it. Moreover, we study the essential characteristics of HMTD and find that all HMTD schemes are in a space spanned by branch parameters. We further propose a multistage HMTD (MHMTD) method to select multiple HMTD schemes in this space to maximize the detection capability. Experiments show that the MHMTD can maximize the detection capability of HMTD in all test systems with high stealthy probability.

IEEE Transactions on Industrial InformaticsVol. 21(4)
Nanyang Technological University (SG), Guangzhou Experimental Station (CN), Xi’an University of Posts and Telecommunications (CN), Xi'an Jiaotong University (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Openalex Percentile: Top 14%
Smart Grid and Power Systems
2.19
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.

On Stealthiness and Effectiveness of Moving Target Defense in Smart Grids — Gaoxi Xiao, Jiazhou Wang, et al. · IEEE Transactions on Industrial Informatics (2025) | TGRS Research Map | TGRS