Hidden Moving Target Defense against False Data Injection in Distribution Network Reconfiguration

Bo Liu; Hongyu Wu; Anil Pahwa; Fei Ding; Erfan Ibrahim; Ting Liu

doi:10.1109/PESGM.2018.8586470

Hidden Moving Target Defense against False Data Injection in Distribution Network Reconfiguration

Bo Liu
, Hongyu Wu
, Anil Pahwa
, Fei Ding
, Erfan Ibrahim
, Ting Liu

Faculty of Electronic and Information Engineering

Kansas State University
National Renewable Energy Laboratory

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

30 Scopus citations

Abstract

This paper introduces Moving Target Defense (MTD) in distribution system against False Data Injection (FDI) attacks on the supervisory control and data acquisition (SCADA) system. Based on the AC power flow model, a hidden MTD (HMTD) strategy is constructed in combination with network reconfiguration by minimizing the system loss and line power flow differences before and after the HMTD. The proposed HMTD-based network reconfiguration is formulated as a mixed-integer nonlinear programming (MINLP) problem. A refined Genetic Algorithm (GA) is proposed to solve it. Numerical test is conducted in a modified IEEE-66 bus system. The simulation results show that the proposed model reduces the power loss introduced by the HMTD as well as yields a stealthy MTD to the attackers. The impact of HMTD on the system performance is also compared with that of the existing MTD strategies.

Original language	English
Title of host publication	2018 IEEE Power and Energy Society General Meeting, PESGM 2018
Publisher	IEEE Computer Society
ISBN (Electronic)	9781538677032
DOIs	https://doi.org/10.1109/PESGM.2018.8586470
State	Published - 21 Dec 2018
Event	2018 IEEE Power and Energy Society General Meeting, PESGM 2018 - Portland, United States Duration: 5 Aug 2018 → 10 Aug 2018

Publication series

Name	IEEE Power and Energy Society General Meeting
Volume	2018-August
ISSN (Print)	1944-9925
ISSN (Electronic)	1944-9933

Conference

Conference	2018 IEEE Power and Energy Society General Meeting, PESGM 2018
Country/Territory	United States
City	Portland
Period	5/08/18 → 10/08/18

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy

Keywords

False data injection
Genetic algorithm
Hidden moving target defense
Network reconfiguration
SCADA.

Access to Document

10.1109/PESGM.2018.8586470

Cite this

Liu, B., Wu, H., Pahwa, A., Ding, F., Ibrahim, E., & Liu, T. (2018). Hidden Moving Target Defense against False Data Injection in Distribution Network Reconfiguration. In 2018 IEEE Power and Energy Society General Meeting, PESGM 2018 Article 8586470 (IEEE Power and Energy Society General Meeting; Vol. 2018-August). IEEE Computer Society. https://doi.org/10.1109/PESGM.2018.8586470

@inproceedings{1f4f6985b1f34e658edb03d4ac769482,

title = "Hidden Moving Target Defense against False Data Injection in Distribution Network Reconfiguration",

abstract = "This paper introduces Moving Target Defense (MTD) in distribution system against False Data Injection (FDI) attacks on the supervisory control and data acquisition (SCADA) system. Based on the AC power flow model, a hidden MTD (HMTD) strategy is constructed in combination with network reconfiguration by minimizing the system loss and line power flow differences before and after the HMTD. The proposed HMTD-based network reconfiguration is formulated as a mixed-integer nonlinear programming (MINLP) problem. A refined Genetic Algorithm (GA) is proposed to solve it. Numerical test is conducted in a modified IEEE-66 bus system. The simulation results show that the proposed model reduces the power loss introduced by the HMTD as well as yields a stealthy MTD to the attackers. The impact of HMTD on the system performance is also compared with that of the existing MTD strategies.",

keywords = "False data injection, Genetic algorithm, Hidden moving target defense, Network reconfiguration, SCADA.",

author = "Bo Liu and Hongyu Wu and Anil Pahwa and Fei Ding and Erfan Ibrahim and Ting Liu",

note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 2018 IEEE Power and Energy Society General Meeting, PESGM 2018 ; Conference date: 05-08-2018 Through 10-08-2018",

year = "2018",

month = dec,

day = "21",

doi = "10.1109/PESGM.2018.8586470",

language = "英语",

series = "IEEE Power and Energy Society General Meeting",

publisher = "IEEE Computer Society",

booktitle = "2018 IEEE Power and Energy Society General Meeting, PESGM 2018",

}

Liu, B, Wu, H, Pahwa, A, Ding, F, Ibrahim, E & Liu, T 2018, Hidden Moving Target Defense against False Data Injection in Distribution Network Reconfiguration. in 2018 IEEE Power and Energy Society General Meeting, PESGM 2018., 8586470, IEEE Power and Energy Society General Meeting, vol. 2018-August, IEEE Computer Society, 2018 IEEE Power and Energy Society General Meeting, PESGM 2018, Portland, United States, 5/08/18. https://doi.org/10.1109/PESGM.2018.8586470

Hidden Moving Target Defense against False Data Injection in Distribution Network Reconfiguration. / Liu, Bo; Wu, Hongyu; Pahwa, Anil et al.
2018 IEEE Power and Energy Society General Meeting, PESGM 2018. IEEE Computer Society, 2018. 8586470 (IEEE Power and Energy Society General Meeting; Vol. 2018-August).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - Hidden Moving Target Defense against False Data Injection in Distribution Network Reconfiguration

AU - Liu, Bo

AU - Wu, Hongyu

AU - Pahwa, Anil

AU - Ding, Fei

AU - Ibrahim, Erfan

AU - Liu, Ting

PY - 2018/12/21

Y1 - 2018/12/21

N2 - This paper introduces Moving Target Defense (MTD) in distribution system against False Data Injection (FDI) attacks on the supervisory control and data acquisition (SCADA) system. Based on the AC power flow model, a hidden MTD (HMTD) strategy is constructed in combination with network reconfiguration by minimizing the system loss and line power flow differences before and after the HMTD. The proposed HMTD-based network reconfiguration is formulated as a mixed-integer nonlinear programming (MINLP) problem. A refined Genetic Algorithm (GA) is proposed to solve it. Numerical test is conducted in a modified IEEE-66 bus system. The simulation results show that the proposed model reduces the power loss introduced by the HMTD as well as yields a stealthy MTD to the attackers. The impact of HMTD on the system performance is also compared with that of the existing MTD strategies.

AB - This paper introduces Moving Target Defense (MTD) in distribution system against False Data Injection (FDI) attacks on the supervisory control and data acquisition (SCADA) system. Based on the AC power flow model, a hidden MTD (HMTD) strategy is constructed in combination with network reconfiguration by minimizing the system loss and line power flow differences before and after the HMTD. The proposed HMTD-based network reconfiguration is formulated as a mixed-integer nonlinear programming (MINLP) problem. A refined Genetic Algorithm (GA) is proposed to solve it. Numerical test is conducted in a modified IEEE-66 bus system. The simulation results show that the proposed model reduces the power loss introduced by the HMTD as well as yields a stealthy MTD to the attackers. The impact of HMTD on the system performance is also compared with that of the existing MTD strategies.

KW - False data injection

KW - Genetic algorithm

KW - Hidden moving target defense

KW - Network reconfiguration

KW - SCADA.

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DO - 10.1109/PESGM.2018.8586470

M3 - 会议稿件

AN - SCOPUS:85060803974

T3 - IEEE Power and Energy Society General Meeting

BT - 2018 IEEE Power and Energy Society General Meeting, PESGM 2018

PB - IEEE Computer Society

T2 - 2018 IEEE Power and Energy Society General Meeting, PESGM 2018

Y2 - 5 August 2018 through 10 August 2018

ER -

Hidden Moving Target Defense against False Data Injection in Distribution Network Reconfiguration

Abstract

Publication series

Conference

UN SDGs

Keywords

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