Abstract
Due to the continuous development of technology, an increasing number of electronic devices are being developed with networking features suitable for connecting to industrial networks. This technological evolution has also made its way to Industrial Control Systems (ICSs) where an increasing number of monitoring and controlling devices have been connected to computer networks facilitating the supervisory level monitoring and control. Evolution in computing and internet technology has encouraged increasing number of ICS to be linked to cyber-world giving rise to a new class of systems called Cyber-Physical System (CPS) which provides several economic and performance-enhancing benefits. However, it also makes ICS more vulnerable to cyber-attacks. The effect of cyber-attacks differs in cyber-physical critical ICS compared to traditional ICT systems as they can cause damage to physical infrastructure posing threats to human health and environment. The complex CPS infrastructure more than ever requires the development of novel security solutions, as these systems are continuously targeted by attacks and intrusions by intelligent adversaries.
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
A.A. Abokifa, K. Haddad, C. Lo, P. Biswas, Real-time identification of cyber-physical attacks on water distribution systems via machine learning-based anomaly detection techniques. J. Water Resour. Plan. Manag. 145(1), 04018089 (2019)
S. Adepu, A. Mathur, Distributed attack detection in a water treatment plant: method and case study. IEEE Trans. Dependable Secure Comput. 18(1), 86–99 (2021)
S.H.M. Ahmad, N. Meskin, Cyber attack detection for a nonlinear binary crude oil distillation column, in 2020 IEEE International Conference on Informatics, IoT, and Enabling Technologies (ICIoT) (2020), pp. 212–218
A. AlDairi, L. Tawalbeh, Cyber security attacks on smart cities and associated mobile technologies. Procedia Comput. Sci. 109, 1086–1091 (2017). 8th International Conference on Ambient Systems, Networks and Technologies, ANT-2017 and the 7th International Conference on Sustainable Energy Information Technology, SEIT 2017, 16–19 May 2017, Madeira, Portugal
R. Bendib, H. Bentarzi, Y. Zennir, Investigation of the effect of design aspects on dynamic control of a binary distillation column, in 2015 4th International Conference on Electrical Engineering (ICEE) (2015), pp. 1–5
M. Elnour, N. Meskin, R. Jain, A dual-isolation-forests-based attack detection framework for industrial control systems. IEEE Access 1 (2020)
M. Elnour, N. Meskin, R. Jain, Application of data-driven attack detection framework for secure operation in smart buildings. Sustain. Cities Soc. 69, 102816 (2021)
A. George, R.M. Francis, Model reference adaptive control of binary distillation column composition using MIT adaptive mechanism. Int. J. Eng. Res. Technol. 4 (2015)
Y. He, G.J. Mendis, J. Wei, Real-time detection of false data injection attacks in smart grid: a deep learning-based intelligent mechanism. IEEE Trans. Smart Grid 8(5), 2505–2516 (2017)
P. Kathel, A.K. Jana, Dynamic simulation and nonlinear control of a rigorous batch reactive distillation. ISA Trans. 49(1), 130–137 (2010)
M. Kravchik, A. Shabtai, Anomaly detection; industrial control systems; convolutional neural networks. CoRR (2018), arXiv:abs/1806.08110
D. Kundur, X. Feng, S. Mashayekh, S. Liu, T. Zourntos, K. Butler-Purry, Towards modelling the impact of cyber attacks on a smart grid. Int. J. Secur. Netw. 6, 2–13 (2011)
M.N. Kurt, O. Ogundijo, C. Li, X. Wang, Online cyber-attack detection in smart grid: a reinforcement learning approach. IEEE Trans. Smart Grid 10(5), 5174–5185 (2019)
D. Li, D. Chen, L. Shi, B. Jin, J. Goh, S. Ng, MAD-GAN: multivariate anomaly detection for time series data with generative adversarial networks. CoRR (2019), arXiv:abs/1901.04997
Q. Lin, S. Adepu, S. Verwer, A. Mathur, Tabor: a graphical model-based approach for anomaly detection in industrial control systems, in Proceedings of the 2018 on Asia Conference on Computer and Communications Security, ASIACCS ’18 (Association for Computing Machinery, New York, NY, USA, 2018), pp. 525–536
M. Lv, W. Yu, Y. Lv, J. Cao, W. Huang, An integral sliding mode observer for cps cyber security attack detection. Chaos: Interdiscip. J. Nonlinear Sci. 29, 043120 (2019)
K. Manandhar, X. Cao, F. Hu, Y. Liu, Detection of faults and attacks including false data injection attack in smart grid using Kalman filter. IEEE Trans. Control Netw. Syst. 1(4), 370–379 (2014)
T. Meraj, S. Sharmin, A. Mahmud, Studying the impacts of cyber-attack on smart grid, in 2015 2nd International Conference on Electrical Information and Communication Technologies (EICT) (2015), pp. 461–466
V.T. Minh, J. Pumwa, Modeling and adaptive control simulation for a distillation column, in 2012 UKSim 14th International Conference on Computer Modelling and Simulation (2012a), pp. 61–65
V. Minh, J. Pumwa, Modeling and control simulation for a condensate distillation column (2012b)
Y. Mo, S. Weerakkody, B. Sinopoli, Physical authentication of control systems: designing watermarked control inputs to detect counterfeit sensor outputs. IEEE Control Syst. Mag. 35(1), 93–109 (2015)
M. Noorizadeh, M. Shakerpour, N. Meskin, D. Unal, K. Khorasani, A cyber-security methodology for a cyber-physical industrial control system testbed. IEEE Access 9, 16 239–16 253 (2021)
A. Nourian, S. Madnick, A systems theoretic approach to the security threats in cyber physical systems applied to stuxnet. IEEE Trans. Dependable Secure Comput. 15(1), 2–13 (2018)
F. Pasqualetti, F. Dorfler, F. Bullo, Attack detection and identification in cyber-physical systems. IEEE Trans. Autom. Control 58, 2715–2729 (2012)
F. Pasqualetti, F. Dorfler, F. Bullo, Control-theoretic methods for cyberphysical security: geometric principles for optimal cross-layer resilient control systems. IEEE Control Syst. Mag. 35(1), 110–127 (2015). (Feb)
G. Radulescu, N. Paraschiv, A. Kienle, An original approach for the dynamic simulation of a crude oil distillation plant 2: setting-up and testing the simulator. Revista de Chimie 58 (2007)
S. Sridhar, M. Govindarasu, Model-based attack detection and mitigation for automatic generation control. IEEE Trans. Smart Grid 5(2), 580–591 (2014)
S.A. Taqvi, L.D. Tufa, S. Muhadizir, Optimization and dynamics of distillation column using aspen plus\(\circ {R}\). Procedia Eng. 148, 978–984 (2016). Proceeding of 4th International Conference on Process Engineering and Advanced Materials (ICPEAM 2016)
S.A. Taqvi, L.D. Tufa, H. Zabiri, S. Mahadzir, A.S. Maulud, F. Uddin, Rigorous dynamic modelling and identification of distillation column using aspen plus, in 2017 IEEE 8th Control and System Graduate Research Colloquium (ICSGRC) (2017), pp. 262–267
W. Weerachaipichasgul, P. Kittisupakorn, A. Saengchan, K. Konakom, I.M. Mujtaba, Batch distillation control improvement by novel model predictive control. J. Ind. Eng. Chem. 16(2), 305–313 (2010)
E. Wijn, Weir flow and liquid height on sieve and valve trays. Chem. Eng. J. 73(3), 191–204 (1999)
T. Zhang, Y. Wang, X. Liang, Z. Zhuang, W. Xu, Cyber attacks in cyber-physical power systems: a case study with GPRS-based SCADA systems, in 2017 29th Chinese Control And Decision Conference (CCDC) (2017), pp. 6847–6852
Z. Zou, Z. Wang, L. Meng, M. Yu, D. Zhao, N. Guo, Modelling and advanced control of a binary batch distillation pilot plant. Chin. Autom. Congr. (CAC) 2017, 2836–2841 (2017)
Acknowledgements
This publication was made possible by the Graduate Sponsorship Research Award (GSRA) award (GSRA4-2- 0518-17083) from the Qatar National Research Fund (QNRF), a member of the Qatar Foundation. The authors would also like to acknowledge the financial support received from NATO under the Emerging Security Challenges Division program.
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2022 The Author(s), under exclusive license to Springer Nature Switzerland AG
About this chapter
Cite this chapter
Ahmad, H.M.S., Meskin, N., Noorizadeh, M. (2022). Cyber-Attack Detection for a Crude Oil Distillation Column. In: Abbaszadeh, M., Zemouche, A. (eds) Security and Resilience in Cyber-Physical Systems. Springer, Cham. https://doi.org/10.1007/978-3-030-97166-3_13
Download citation
DOI: https://doi.org/10.1007/978-3-030-97166-3_13
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-97165-6
Online ISBN: 978-3-030-97166-3
eBook Packages: EngineeringEngineering (R0)