Cyber Security of Critical Infrastructures



Modern Supervisory Control and Data Acquisition (SCADA) systems are essential for monitoring and managing electric power generation, transmission and distribution. In the age of the Internet of Things, SCADA has evolved into big, complex and distributed systems that are prone to conventional in addition to new threats. Many security methods can be applied to such systems, taking in mind that both high efficiency, real time intrusion identification and low overhead are required.


SCADA, IACS, Cyber-security


Critical Infrastructure Security


Elsevier ICT Express - Special Issue on CI & Smart Grid Cyber Security , Eun-Soo Kim, February 2018


Cited by

Year 2019 : 17 citations

 Handa A, Sharma A, Shukla SK. Machine learning in cybersecurity: A review. Wiley WIREs - Data Mining and Knowledge Discovery. 2019; DOI:10.1002/widm.1306

 Hu, Y., Li, H., Yang, H. et al., "Detecting stealthy attacks against industrial control systems based on residual skewness analysis", EURASIP J Wireless Com Network (2019) 2019: 74. DOI: 10.1186/s13638-019-1389-1

 Hu, Yan & Li, Hong & H. Luan, Tom & Yang, An & Sun, Limin & Wang, Zhiliang & Wang, Rui. (2018). Detecting stealthy attacks on industrial control systems using a permutation entropy-based method. Future Generation Computer Systems. 10.1016/j.future.2018.07.027.

 R. Jidin, S. N. Tukijan, I. Al-Bahadly, N. Jamil and Q. S. Qassim, "Prototyping a Lightweight Encryption on a Field Programmable Gate Array for Securing Tele-Control Data," 2018 8th IEEE International Conference on Control System, Computing and Engineering (ICCSCE), Penang, Malaysia, 2018, pp. 180-185. DOI: 10.1109/ICCSCE.2018.8685001

 Socarrás, H.E., Santana, I., "Cyber security for the industrial control system of the elquim’s chlorine plant [Ciberseguridad del sistema de control industrial de la planta cloro-sosa ELQUIM]", 2019, RISTI - Revista Iberica de Sistemas e Tecnologias de Informacao, 2019 (32), pp. 83-96. DOI; 10.17013/risti.32.83–96

 Mikhail Gurin, Alexey Vulfin, Vladimir Vasilyev, Andrey Nikonov, "Intrusion detection system on the basis of data mining
algorithms in the industrial network", in Proceedings of the Data Science Session at the V International Conference on Information Technology and Nanotechnology, Samara, Russia, May 21-24, 2019. Available at:

 W. Li, J. Jin and J. Lee, "Analysis of Botnet Domain Names for IoT Cybersecurity," in IEEE Access, vol. 7, pp. 94658-94665, 2019. doi: 10.1109/ACCESS.2019.2927355

 R. Colelli, S. Panzieri and F. Pascucci, "Securing connection between IT and OT: the Fog Intrusion Detection System prospective," 2019 II Workshop on Metrology for Industry 4.0 and IoT (MetroInd4.0&IoT), Naples, Italy, 2019, pp. 444-448. DOI: 10.1109/METROI4.2019.8792884

 Börner, Johannes and Scheurich, Simon and Steinke, Florian (2019): Nonlinear consensus for improved resilience of distributed secondary frequency control. Bucharest, Romania, In: 2019 IEEE PES Innovative Smart Grid Technologies Europe (ISGT-Europe), Bucharest, Romania, September 29 to October 2, 2019.

 Viganò, Eleonora & Loi, Michele & Yaghmaei, Emad. (2019). Cybersecurity of critical infrastructure, in The Ethics of Cybersecurity, Springer, september 2019.

 Veneta Yosifova, Roumen Trifonov, Antoniya Tasheva, and Ognian Nakov. 2019. Trends Review of the Contemporary Security Problems in the Cyberspace. In Proceedings of the 9th Balkan Conference on Informatics (BCI'19). ACM, New York, NY, USA, Article 10, 4 pages. DOI:

 Carreño Pérez, Juan Carlos. "Metodología para evaluación de ciber vulnerabilidad en sistemas de transmisión de energía eléctrica “EVULCIB”, estudio de caso subestación eléctrica de 230kV ubicada en la ciudad de Bogotá-Colombia.", MSc thesis, Universidad Distrital Francisco Jose? De Caldas, Colombia, 2019.

 Serrano, Will. "Deep Reinforcement Learning Algorithms in Intelligent Infrastructure." Infrastructures 4.3 (2019): 52. DOI: 0.3390/infrastructures4030052

 Vavra J., Hromada M. (2019) Optimization of the Novelty Detection Model Based on LSTM Autoencoder for ICS Environment. In: Silhavy R., Silhavy P., Prokopova Z. (eds) Intelligent Systems Applications in Software Engineering. CoMeSySo 2019 2019. Advances in Intelligent Systems and Computing, vol 1046. Springer, Cham. DOI: 10.1007/978-3-030-30329-7_28

 Mazzoccoli, A. and Naldi, M. (2019), Robustness of Optimal Investment Decisions in Mixed Insurance/Investment Cyber Risk Management. Risk Analysis. DOI:10.1111/risa.13416

 R. Kekoa Koehler, "When the Lights Go Out: Vulnerabilities to US Critical Infrastructure,
the Russian Cyber Threat, and a New Way Forward", Georgetown Security Studies Review, Volume 7, Issue 1
January 2019. ISSN 2474-8552 (print); ISSN 2474-8560 (online). URL:

 Álvaro Roberto Rojas Castro, "Protección en infraestructuras críticas. Análisis de seguridad de los sistemas de control industrial", MsC thesis, Máster Interuniversitario en Seguridad de las Tecnologías de la Información y de las Comunicaciones (MISTIC), Universitat Oberta de Catalunya, January 2019. Available at:

Year 2018 : 6 citations

 Lu KC., Liu IH., Sun MW., Li JS. (2019) A Survey on SCADA Security and Honeypot in Industrial Control System. In: Saeed F., Gazem N., Mohammed F., Busalim A. (eds) Recent Trends in Data Science and Soft Computing. IRICT 2018. Advances in Intelligent Systems and Computing, vol 843. Springer, Cham. DOI: 10.1007/978-3-319-99007-1_56

 Raposo, D.; Rodrigues, A.; Sinche, S.; Sá Silva, J.; Boavida, F., "Industrial IoT Monitoring: Technologies and Architecture Proposal". Sensors 2018, 18, 3568. DOI: 10.3390/s18103568

 Nicol, Cameron, "Cybersecurity and national resilience in Estonia", MSc Thesis in International Security, Intelligence
and Strategic Studies (SECINTEL). May 2018. DOI: 20.500.11956/101734.

 Raposo, Duarte & Rodrigues, André & Sinche, Soraya & Sá Silva, Jorge & Boavida, Fernando. (2018). Securing WirelessHART: Monitoring, Exploring and Detecting New Vulnerabilities. 1-9. 10.1109/NCA.2018.8548060.

 Sameera, N. (2018). Protocol-Specific Intrusion Detection System using KNN Classifier. International Journal for Research in Applied Science and Engineering Technology. 6. 292-299. 10.22214/ijraset.2018.5049.

 Vavra, J[an] & Hromada, M[artin] (2018). Comparative Study of Feature Selection Techniques Respecting Novelty Detection in the Industrial Control System Environment, Proceedings of the 29th DAAAM International Symposium, pp.1084-1091, B. Katalinic (Ed.), Published by DAAAM International, ISBN 978-3-902734-20-4, ISSN 1726-9679, Vienna, Austria.
DOI: 10.2507/29th.daaam.proceedings.155