Set-theoretic detection of data corruption attacks on cyber physical power systems

Efstathios Kontouras, Antonios Tzes, Leonidas Dritsas

    Research output: Contribution to journalArticle

    Abstract

    This paper addresses a set-theoretic method for the detection of data corruption cyber-attacks on the load frequency control loop of a networked power system. The system consists of several interconnected control areas forming a power grid. Based on the overall discrete-time network dynamics, a convex and compact polyhedral robust invariant set is extracted and is used as a set-induced anomaly detector. If the state vector exits the invariant set, then an alarm will be activated, and the potential threat is considered disclosed. The attack scenario used to assess the efficiency of the proposed anomaly detector concerns corrupted frequency sensor measurements transmitted to the automatic generation control unit of a compromised control area. Simulation studies highlight the ability of a set-theoretic approach to disclose persistent and intermittent attack patterns even when they occur at the same time with changes in the power load demand.

    Original languageEnglish (US)
    Pages (from-to)872-886
    Number of pages15
    JournalJournal of Modern Power Systems and Clean Energy
    Volume6
    Issue number5
    DOIs
    StatePublished - Sep 1 2018

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    Detectors
    Sensors

    Keywords

    • Cyber-attacks
    • Load frequency control
    • Power systems
    • Set-theoretic methods

    ASJC Scopus subject areas

    • Renewable Energy, Sustainability and the Environment
    • Energy Engineering and Power Technology

    Cite this

    Set-theoretic detection of data corruption attacks on cyber physical power systems. / Kontouras, Efstathios; Tzes, Antonios; Dritsas, Leonidas.

    In: Journal of Modern Power Systems and Clean Energy, Vol. 6, No. 5, 01.09.2018, p. 872-886.

    Research output: Contribution to journalArticle

    Kontouras, Efstathios ; Tzes, Antonios ; Dritsas, Leonidas. / Set-theoretic detection of data corruption attacks on cyber physical power systems. In: Journal of Modern Power Systems and Clean Energy. 2018 ; Vol. 6, No. 5. pp. 872-886.
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