Skip to Main content Skip to Navigation
Theses

Attack Modelling and Detection in Distributed and Cooperative Controlled Microgrid Systems

Mingxiao Ma 1 
1 RESIST - Resilience and Elasticity for Security and ScalabiliTy of dynamic networked systems
Inria Nancy - Grand Est, LORIA - NSS - Department of Networks, Systems and Services
Abstract : Modern low-voltage microgrid systems rely on distributed and cooperative control approaches to guarantee safe and reliable operational decisions of their inverter-based distributed generators (DGs). However, many sophisticated cyber-attacks can target these systems, deceive their traditional detection methods and cause a severe impact on the power infrastructure. In this thesis, we systematically study the vulnerabilities and threats of distributed controlled microgrid systems. We design a novel attack named "measurement-as-reference" (MaR) attack and take it as a typical stealthy attack example to theoretically analyze the attack impact on the microgrid system and use numerical simulation results to verify the analysis. We provide mathematical models of possible false data injection (FDI) and denial of service (DoS) attacks in a representative distributed and cooperative controlled microgrid system. We propose a secure control framework with an attack detection module based on machine learning techniques. To validate the effectiveness of this framework, we implement two typical attacks, MaR attack and delay injection attack, on a hardware platform modeled after a microgrid system. We collect datasets from the platform and validate the performance of multiple categories of machine learning algorithms to detect such attacks. Our results show that tree-based classifiers (Decision Tree, Random Forest and AdaBoost) outperform other algorithms and achieve excellent performance in detecting normal behavior, delay injection and false data attacks.
Complete list of metadata

https://hal.univ-lorraine.fr/tel-03356948
Contributor : Thèses UL Connect in order to contact the contributor
Submitted on : Tuesday, September 28, 2021 - 3:25:02 PM
Last modification on : Friday, February 4, 2022 - 3:29:53 AM
Long-term archiving on: : Wednesday, December 29, 2021 - 6:44:37 PM

File

DDOC_T_2021_0111_MA.pdf
Files produced by the author(s)

Identifiers

  • HAL Id : tel-03356948, version 1

Citation

Mingxiao Ma. Attack Modelling and Detection in Distributed and Cooperative Controlled Microgrid Systems. Computer Science [cs]. Université de Lorraine, 2021. English. ⟨NNT : 2021LORR0111⟩. ⟨tel-03356948⟩

Share

Metrics

Record views

129

Files downloads

170