Cyber attack localization in smart grids by graph modulation

Elisabeth Drayer, Tirza Routtenberg

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

4 Scopus citations

Abstract

In this brief announcement we present our ongoing work to localize “false data injection” (FDI) attacks on the system state of modern power systems, better known as smart grids. Because of their exceptional importance for our society and together with the increasing presence of information and telecommunication (ICT) components, these power systems are a vulnerable target for cyber attacks. In our method, we represent the power system as a graph and use a generalized modulation operator that is applied on the states of the system. Our preliminary results indicate that attacked grid states exhibit specific modulation patterns that facilitate the localization of the attacks on the particular buses of the grid. This approach is demonstrated by several case study simulations.

Original languageEnglish
Title of host publicationCyber Security Cryptography and Machine Learning - 3rd International Symposium, CSCML 2019, Proceedings
EditorsShlomi Dolev, Danny Hendler, Sachin Lodha, Moti Yung
PublisherSpringer Verlag
Pages97-100
Number of pages4
ISBN (Electronic)978-3-030-20951-3
ISBN (Print)9783030209506
DOIs
StatePublished - 19 May 2019
Event3rd International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2019 - Beer Sheva, Israel
Duration: 27 Jun 201928 Jun 2019

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11527 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference3rd International Symposium on Cyber Security Cryptography and Machine Learning, CSCML 2019
Country/TerritoryIsrael
CityBeer Sheva
Period27/06/1928/06/19

Keywords

  • Anomaly detection
  • False data injection (FDI) attacks
  • Graph signal processing
  • Laplacian matrix
  • Smart grid

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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