Computational intelligence algorithms analysis for smart grid cyber security

  • Authors:

  • Yong Wang;Da Ruan;Jianping Xu;Mi Wen;Liwen Deng

  • Affiliations:

  • ,Department of Computers Science and Technology, Shanghai University of Electric Power, Shanghai, China;Belgian Nuclear Research Centre, Mol, Belgium;Department of Computers Science and Technology, Shanghai University of Electric Power, Shanghai, China;Department of Computers Science and Technology, Shanghai University of Electric Power, Shanghai, China;Shanghai Changjiang Computer Group Corporation, China

  • Venue:
  • ICSI'10 Proceedings of the First international conference on Advances in Swarm Intelligence - Volume Part II
  • Year:
  • 2010

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Abstract

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.