Computational intelligence algorithms analysis for smart grid cyber security

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

doi:10.1007/978-3-642-13498-2_11

Computational intelligence algorithms analysis for smart grid cyber security

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

Research output › peer-review

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.

Original language	English
Title of host publication	Advances in Swarm Intelligence
Place of Publication	Heidelberg, Germany
Pages	77-84
Number of pages	8
Volume	2
Edition	PART 2
DOIs	https://doi.org/10.1007/978-3-642-13498-2_11
State	Published - 2010
Event	First International Conference in Swarm Intelligence - ICSI, Beijing Duration: 12 Jun 2010 → 15 Jun 2010

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Number	PART 2
Volume	6146 LNCS
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

Conference

Conference	First International Conference in Swarm Intelligence
Country/Territory	China
City	Beijing
Period	2010-06-12 → 2010-06-15

ASJC Scopus subject areas

Theoretical Computer Science
General Computer Science

Access to Document

10.1007/978-3-642-13498-2_11License: Unspecified

Cite this

Wang, Y., Ruan, D., Xu, J., Wen, M., & Deng, L. (2010). Computational intelligence algorithms analysis for smart grid cyber security. In Advances in Swarm Intelligence (PART 2 ed., Vol. 2, pp. 77-84). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6146 LNCS, No. PART 2).. https://doi.org/10.1007/978-3-642-13498-2_11

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keywords = "Smart Grid, Cyber Security, Computational Intelligence",

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Wang, Y, Ruan, D, Xu, J, Wen, M & Deng, L 2010, Computational intelligence algorithms analysis for smart grid cyber security. in Advances in Swarm Intelligence. PART 2 edn, vol. 2, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), no. PART 2, vol. 6146 LNCS, Heidelberg, Germany, pp. 77-84, First International Conference in Swarm Intelligence, Beijing, China, 2010-06-12. https://doi.org/10.1007/978-3-642-13498-2_11

Computational intelligence algorithms analysis for smart grid cyber security. / Wang, Yong; Ruan, Da; Xu, Jianping et al.
Advances in Swarm Intelligence. Vol. 2 PART 2. ed. Heidelberg, Germany, 2010. p. 77-84 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 6146 LNCS, No. PART 2).

Research output › peer-review

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T1 - Computational intelligence algorithms analysis for smart grid cyber security

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AB - 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.

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Wang Y, Ruan D, Xu J, Wen M, Deng L. Computational intelligence algorithms analysis for smart grid cyber security. In Advances in Swarm Intelligence. PART 2 ed. Vol. 2. Heidelberg, Germany. 2010. p. 77-84. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); PART 2). doi: 10.1007/978-3-642-13498-2_11