Set-Induced Anomaly Detectors for Networked Power Systems under Bias Injection Cyber-Attacks

Efstathios Kontouras, Anthony Tzes, Leonidas Dritsas

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

This paper addresses the concept of a set-induced anomaly detector of bias injection cyber-attacks affecting the load frequency control loop of a networked power system. An adversary corrupts the frequency sensor measurements causing abnormal system behavior. A set-theoretic methodology is used for the extraction of a convex and compact polyhedral robust invariant set under the overall discretized network dynamics. An attack is considered disclosed when the state vector exits the invariant set. Simulation studies demonstrate the impact of an intermittent attack on a two-area power plant and provide an assessment of the proposed detector, when the attack happens simultaneously with changes in the power load demand.

Original languageEnglish (US)
Title of host publication2018 European Control Conference, ECC 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages2472-2475
Number of pages4
ISBN (Electronic)9783952426982
DOIs
StatePublished - Nov 27 2018
Event16th European Control Conference, ECC 2018 - Limassol, Cyprus
Duration: Jun 12 2018Jun 15 2018

Publication series

Name2018 European Control Conference, ECC 2018

Conference

Conference16th European Control Conference, ECC 2018
CountryCyprus
CityLimassol
Period6/12/186/15/18

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Control and Optimization

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