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JCR Impact Factor: 0.650
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PUBLISHER

Stefan cel Mare
University of Suceava
Faculty of Electrical Engineering and
Computer Science
13, Universitatii Street
Suceava - 720229
ROMANIA

Print ISSN: 1582-7445
Online ISSN: 1844-7600
WorldCat: 643243560
doi: 10.4316/AECE


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2019-Jun-20
Clarivate Analytics published the InCites Journal Citations Report for 2018. The JCR Impact Factor of Advances in Electrical and Computer Engineering is 0.650, and the JCR 5-Year Impact Factor is 0.639.

2018-May-31
Starting today, the minimum number a pages for a paper is 8, so all submitted papers should have 8, 10 or 12 pages. No exceptions will be accepted.

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  3/2019 - 8

A Fuzzy AHP Approach for Security Risk Assessment in SCADA Networks

MARKOVIC-PETROVIC, J. D. See more information about MARKOVIC-PETROVIC, J. D. on SCOPUS See more information about MARKOVIC-PETROVIC, J. D. on IEEExplore See more information about MARKOVIC-PETROVIC, J. D. on Web of Science, STOJANOVIC, M. D. See more information about   STOJANOVIC, M. D. on SCOPUS See more information about   STOJANOVIC, M. D. on SCOPUS See more information about STOJANOVIC, M. D. on Web of Science, BOSTJANCIC RAKAS, S. V. See more information about BOSTJANCIC RAKAS, S. V. on SCOPUS See more information about BOSTJANCIC RAKAS, S. V. on SCOPUS See more information about BOSTJANCIC RAKAS, S. V. on Web of Science
 
Click to see author's profile in See more information about the author on SCOPUS SCOPUS, See more information about the author on IEEE Xplore IEEE Xplore, See more information about the author on Web of Science Web of Science

Download PDF pdficon (280 KB) | Citation | Downloads: 72 | Views: 119

Author keywords
decision making, fuzzy logic, information security, risk analysis, SCADA systems

References keywords
security(15), systems(9), scada(9), risk(8), cyber(8), assessment(7), control(5), industrial(4), fuzzy(4)
Blue keywords are present in both the references section and the paper title.

About this article
Date of Publication: 2019-08-31
Volume 19, Issue 3, Year 2019, On page(s): 69 - 74
ISSN: 1582-7445, e-ISSN: 1844-7600
Digital Object Identifier: 10.4316/AECE.2019.03008
Web of Science Accession Number: 000486574100008
SCOPUS ID: 85072203058

Abstract
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In this paper we propose a new method for security risk assessment in Supervisory Control and Data Acquisition (SCADA) networks. The method consists of the three phases, namely the objective phase, the subjective phase and the final assessment phase. The objective phase deals with the analysis of SCADA historical data. The subjective phase takes into account the experience of relevant experts. The final assessment phase takes into account outputs from both the objective and subjective phases. Fuzzy logic has been applied in all three phases, while analytic hierarchy process (AHP) has been used in subjective phase, due to its suitability to evaluate the experts' competency. The method is evaluated on a case study regarding the real run-off-river hydropower plant. Evaluation results have clearly indicated benefits of the proposed method in comparison with the purely objective approach, in terms of more precise risk assessment and higher return on security investment.


References | Cited By  «-- Click to see who has cited this paper

[1] M. Stojanovic, S. Bostjancic Rakas, J. Markovic-Petrovic, "Cloud-based SCADA systems: Cyber security considerations and future challenges," invited paper, in Proc. 4th Virtual Int. Conf. Science, Technology and Management in Energy, pp. 253-260, October 2018. [Online] Available: Temporary on-line reference link removed - see the PDF document

[2] B. Zhu, A. Joseph, S. Sastry, "A taxonomy of cyber attacks on SCADA systems," in Proc. 2011 International Conference on the Internet of Things and the 4th International Conference on Cyber, Physical and Social Computing, 2011, pp. 380-388.
[CrossRef] [SCOPUS Times Cited 201]


[3] A. Nicholson, S. Webber, S. Dyer, T. Patel, H. Janicke, "SCADA security in the light of cyber-warfare," Computers & Security, vol. 31, no. 4, pp. 418-436, Jun. 2012.
[CrossRef] [Web of Science Times Cited 113] [SCOPUS Times Cited 160]


[4] D. Ding, Q.-L. Han, Y. Xiang, X. Ge, X.-M. Zhang, "A survey on security control and attack detection for industrial cyber-physical systems," Neurocomputing, vol. 275, pp. 1674-1683, Jan. 2018.
[CrossRef] [Web of Science Times Cited 71] [SCOPUS Times Cited 92]


[5] C. Queiroz, A. Mahmood, J. Hu, Z. Tari, X. Yu, "Building a SCADA security testbed," in Proc. 2009 Third International Conference on Network and System Security, IEEE, 2009, pp. 357-364.
[CrossRef] [SCOPUS Times Cited 57]


[6] J. Markovic-Petrovic, M. Stojanovic, "Analysis of SCADA system vulnerabilities to DDoS attacks," in Proc. 2013 11th International Conference on Telecommunications in Modern Satellite, Cable and Broadcasting Services (TELSIKS), 2013, vol. 02, pp. 591-594.
[CrossRef] [SCOPUS Times Cited 9]


[7] S. Asri, B. Pranggono, "Impact of distributed denial-of-service attack on advanced metering infrastructure," Wireless Personal Communications, vol. 83, no. 3, pp. 2211-2223, Aug. 2015.
[CrossRef] [Web of Science Times Cited 13] [SCOPUS Times Cited 19]


[8] J. Gao et al., "SCADA communication and security issues," Security and Communication Networks, vol. 7, no. 1, pp. 175-194, Jan. 2014.
[CrossRef] [Web of Science Times Cited 28] [SCOPUS Times Cited 38]


[9] R. S. Ross, "Guide for conducting risk assessments," National Institute of Standards and Technology, NIST Special Publication (SP) 800-30 Rev. 1, Sep. 2012.

[10] J. D. Markovic-Petrovic, M. D. Stojanovic, "An improved risk assessment method for SCADA information security," Elektronika ir Elektrotechnika, vol. 20, no. 7, pp. 69-72, Sep. 2014.
[CrossRef] [Web of Science Times Cited 5] [SCOPUS Times Cited 5]


[11] Y. Cherdantseva et al., "A review of cyber security risk assessment methods for SCADA systems," Computers & Security, vol. 56, pp.1-27, Feb. 2016.
[CrossRef] [Web of Science Times Cited 85] [SCOPUS Times Cited 128]


[12] P. A. S. Ralston, J. H. Graham, J. L. Hieb, "Cyber security risk assessment for SCADA and DCS networks," ISA Transactions, vol. 46, no. 4, pp. 583-594, Oct. 2007.
[CrossRef] [Web of Science Times Cited 93] [SCOPUS Times Cited 136]


[13] J. Yan, M. Govindarasu, C. Liu, U. Vaidya, "A PMU-based risk assessment framework for power control systems," in Proc. 2013 IEEE Power Energy Society General Meeting, 2013, pp. 1-5.
[CrossRef] [SCOPUS Times Cited 10]


[14] M. Gul, A. F. Guneri, "A fuzzy multi criteria risk assessment based on decision matrix technique: A case study for aluminum industry," Journal of Loss Prevention in the Process Industries, vol. 40, pp. 89-100, Mar. 2016.
[CrossRef] [Web of Science Times Cited 45] [SCOPUS Times Cited 47]


[15] Q. Zhang, C. Zhou, Y. Tian, N. Xiong, Y. Qin, B. Hu, "A fuzzy probability Bayesian network approach for dynamic cybersecurity risk assessment in industrial control systems," IEEE Transactions on Industrial Informatics, vol. 14, no. 6, pp. 2497-2506, Jun. 2018.
[CrossRef] [Web of Science Times Cited 6] [SCOPUS Times Cited 7]


[16] Y. Duan, Y. Cai, Z. Wang, X. Deng, "A novel network security risk assessment approach by combining subjective and objective weights under uncertainty," Applied Sciences, vol. 8, no. 3, p. 428, Mar. 2018.
[CrossRef] [Web of Science Times Cited 7] [SCOPUS Times Cited 9]


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[CrossRef]


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[CrossRef]


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[20] H. Zhang, D. Liu, Fuzzy Modeling and Fuzzy Control, Birkhäuser Basel, pp. 139-145, 2006.
[CrossRef]


[21] B. Galloway, G. Hancke, "Introduction to industrial control networks," IEEE Communications Surveys and Tutorials, vol. 15, no. 2, pp. 860-880, 2013.
[CrossRef] [Web of Science Times Cited 145] [SCOPUS Times Cited 187]


[22] R. Mitchell, I.-R. Chen, "A survey of intrusion detection techniques for cyber physical systems," ACM Computing Surveys, vol. 46, no. 4, pp. 55:1-55:29, Mar. 2014.
[CrossRef] [Web of Science Times Cited 142] [SCOPUS Times Cited 199]




References Weight

Web of Science® Citations for all references: 753 TCR
SCOPUS® Citations for all references: 1,304 TCR

Web of Science® Average Citations per reference: 33 ACR
SCOPUS® Average Citations per reference: 57 ACR

TCR = Total Citations for References / ACR = Average Citations per Reference

We introduced in 2010 - for the first time in scientific publishing, the term "References Weight", as a quantitative indication of the quality ... Read more

Citations for references updated on 2019-10-15 17:21 in 133 seconds.




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Faculty of Electrical Engineering and Computer Science
Stefan cel Mare University of Suceava, Romania


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