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

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

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

29 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 languageEnglish
Title of host publication2018 IEEE Power and Energy Society General Meeting, PESGM 2018
PublisherIEEE Computer Society
ISBN (Electronic)9781538677032
DOIs
StatePublished - 21 Dec 2018
Event2018 IEEE Power and Energy Society General Meeting, PESGM 2018 - Portland, United States
Duration: 5 Aug 201810 Aug 2018

Publication series

NameIEEE Power and Energy Society General Meeting
Volume2018-August
ISSN (Print)1944-9925
ISSN (Electronic)1944-9933

Conference

Conference2018 IEEE Power and Energy Society General Meeting, PESGM 2018
Country/TerritoryUnited States
CityPortland
Period5/08/1810/08/18

Keywords

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

Fingerprint

Dive into the research topics of 'Hidden Moving Target Defense against False Data Injection in Distribution Network Reconfiguration'. Together they form a unique fingerprint.

Cite this