Abstract
With the frequent occurrence of cyber attacks in recent years, cyber attacks have become a major factor affecting the security and reliability of power SCADA. We urgently need an effective SCADA risk assessment algorithm to quantify the value at risk. However, traditional algorithms have the shortcomings of excessive parsing variables and inefficient sampling. Existing improved algorithms are far from the optimal distribution of the sampling density function. In this paper, we propose an optimal sampling algorithm and a selective parsing algorithm and combine them into an improved hybrid algorithm to solve the problems. The experimental results show that the improved hybrid algorithm not only improves the parsing and sampling efficiency, but also realizes the optimal distribution of the sampling density function and improves the accuracy of the assessment index. The assessment indexs accurately quantify the risk values of three widely used cyber attacks.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Darshana, U., et al.: An efficient key management and multi-layered security framework for SCADA systems. IEEE Trans. Netw. Serv. Manage. 19(1), 642–660 (2021)
He, Hailei., et al.: Reliability evaluation based on modified latin hypercube sampling and minimum load-cutting method. In: 2015 5th International Conference on Electric Utility Deregulation and Restructuring and Power Technologies (DRPT). IEEE, 2015
Gonzalez-Fernandez, R.A., Leite da Silva, A.M.: Reliability assessment of time-dependent systems via sequential cross-entropy Monte Carlo simulation. IEEE Trans. Power Syst. 26(4), 2381–2389 (2011)
Bie, Z., Wang, X.: The application of Monte Carlo method to reliability evaluation of power systems. Autom. Electr. Power Syst. 21(6), 68–75 (1997)
Roslan, N.N.R.B., Fauzi, N.F.B.M., Ridzuan, M.I.M.: Sequential and nonsequential monte carlo in assessing reliability performance of distribution network. In: 2020 Emerging Technology in Computing, Communication and Electronics (ETCCE). IEEE (2020)
Zhang, K., et al.: Improved sequential monte carlo method approach to substation connection reliability assessment. In: 2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2). IEEE (2020)
Wu, L., et al.: Reliability assessment of AC/DC hybrid distribution network based on sequential monte carlo method. In: 2020 5th Asia Conference on Power and Electrical Engineering (ACPEE). IEEE (2020)
Weibo, L., et al.: Risk assessment technology of ship power system based on improved time series algorithm. In: 2020 7th International Conference on Information Science and Control Engineering (ICISCE). IEEE (2020)
Li, L., et al.: Risk assessment for renewable energy penetrated power systems considering battery and hydrogen storage systems. In: 2021 Power System and Green Energy Conference (PSGEC). IEEE (2021)
Tang, S., Liu, Z., Wang, L.: Power system reliability analysis considering external and insider attacks on the SCADA system. In: 2020 IEEE/PES Transmission and Distribution Conference and Exposition (T &D). IEEE (2020)
Liu, J., Shen, H., Yang, F.: Reliability evaluation of distribution network power supply based on improved sampling monte carlo method. In: 2020 5th Asia Conference on Power and Electrical Engineering (ACPEE). IEEE (2020)
Bavajigari, S.K.K., Singh, C.: Investigation of computational advantage of using importance sampling in monte carlo simulation. In: 2019 North American Power Symposium (NAPS). IEEE (2019)
Guo, J., et al.: Security risk assessment of power system based on latin hypercube sampling and daily peak load forecasting. In: 2020 IEEE 4th Conference on Energy Internet and Energy System Integration (EI2). IEEE (2020)
Aibin, L., Wenyi, L.: Reliability evaluation of distribution network with distributed generation based on latin hypercube sequential sampling. In: 2020 3rd International Conference on Electron Device and Mechanical Engineering (ICEDME). IEEE (2020)
Miller, B., Rowe, D.: A survey SCADA of and critical infrastructure incidents. In: Proceedings of the 1st Annual Conference on Research in Information Technology (2012)
RISI-The Repository of Industrial Security Incidents, Apr 2020. [online] Available: http://www.risidata.com/
Pliatsios, D., et al.: A survey on SCADA systems: secure protocols, incidents, threats and tactics. IEEE Commun. Surv. Tutorials 22(3), 1942–1976 (2020)
Moore, D., et al.: Inside the slammer worm. IEEE Secur. Priv. 1(4), 33–39 (2003)
Levy, E.: The making of a spam zombie army. dissecting the Sobig worms. IEEE Secur. Priv. 1(4), 58–59 (2003)
Langner, R.: Stuxnet: dissecting a cyberwarfare weapon. IEEE Secur. Priv. 9(3), 49–51 (2011)
Samdarshi, R., Sinha, N., Tripathi, P.: A triple layer intrusion detection system for SCADA security of electric utility. In: 2015 annual IEEE India Conference (INDICON). IEEE (2015)
Stamp, J., McIntyre, A., Ricardson, B.: Reliability impacts from cyber attack on electric power systems. In: 2009 IEEE/PES Power Systems Conference and Exposition. IEEE (2009)
The UNSW-NB15 Dataset, Intelligent Security Group UNSW Canberra, June 2021 [online] Available: https://research.unsw.edu.au/projects/unsw-nb15-dataset
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering
About this paper
Cite this paper
Yenan, C., Tinghui, L., Linsen, L., Han, Z. (2022). A Novel Risk Assessment Method Based on Hybrid Algorithm for SCADA. In: Gao, H., Wang, X., Wei, W., Dagiuklas, T. (eds) Collaborative Computing: Networking, Applications and Worksharing. CollaborateCom 2022. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 461. Springer, Cham. https://doi.org/10.1007/978-3-031-24386-8_1
Download citation
DOI: https://doi.org/10.1007/978-3-031-24386-8_1
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-031-24385-1
Online ISBN: 978-3-031-24386-8
eBook Packages: Computer ScienceComputer Science (R0)