Computational intelligence algorithms analysis for smart grid cyber security

Yong Wang, Da Ruan, Jianping Xu, Mi Wen, Liwen Deng

    Research outputpeer-review


    The cyber attack risks are threatening the smart grid security. Malicious worm could spread from meter to meter to take out power in a simulated attack. The North American Electric Reliability Corporation (NERC) has thus developed several iterations of cyber security standards. According to the NERC cyber standards CIP-002-2 requirements, in this paper, we present cyber security risk analysis using computational intelligence methods and review on core methods, such as in risk assessment HHM, IIM, RFRM algorithms, fault analysis FTA, ETA, FMEA, FMECA algorithms, fuzzy sets, intrusion detection systems, artificial neural networks and artificial immune systems. Through the analysis of the core computational intelligence algorithms used in the smart grid cyber security in power system network security lab, we clearly defined existing smart grid research challenges.

    Original languageEnglish
    Title of host publicationAdvances in Swarm Intelligence
    Place of PublicationHeidelberg, Germany
    Number of pages8
    EditionPART 2
    StatePublished - 2010
    EventFirst International Conference in Swarm Intelligence - ICSI, Beijing
    Duration: 12 Jun 201015 Jun 2010

    Publication series

    NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
    NumberPART 2
    Volume6146 LNCS
    ISSN (Print)0302-9743
    ISSN (Electronic)1611-3349


    ConferenceFirst International Conference in Swarm Intelligence

    ASJC Scopus subject areas

    • Theoretical Computer Science
    • General Computer Science

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