A Modular Hybrid Learning Approach for Black-Box Security Testing of CPS
Pages 196 - 216
Abstract
Evaluating the security of Cyber-Physical Systems (CPS) is challenging, mainly because it brings risks that are not acceptable in mission-critical systems like Industrial Control Systems (ICS). Model-based approaches help to address such challenges by keeping the risk associated with testing low. This paper presents a novel modelling framework and methodology that can easily be adapted to different CPS. Based on our experiments, HybLearner takes less than 140 s to build a model from historical data of a real-world water treatment testbed, and HybTester can simulate accurately about 60 min ahead of normal behaviour of the system including transitions of control strategies. We also introduce a security metrics (time-to-critical-state) that gives a measurement of how fast the system might reach a critical state, which is one of the use cases of the proposed framework to build a model-based attack detection mechanism.
References
[1]
Adepu, S., Mathur, A.: An investigation into the response of a water treatment system to cyber attacks. In: 2016 IEEE 17th International Symposium on High Assurance Systems Engineering (HASE) (2016)
[2]
Alur R Principles of Cyber-Physical Systems 2015 Cambridge MIT Press
[3]
Carcano A, Coletta A, Guglielmi M, Masera M, Fovino IN, and Trombetta A A multidimensional critical state analysis for detecting intrusions in SCADA systems IEEE Trans. Ind. Inform. 2011 7 179-186
[4]
Cárdenas, A.A., Amin, S., Lin, Z.S., Huang, Y.L., Huang, C.Y., Sastry, S.: Attacks against process control systems: risk assessment, detection, and response. In: Proceedings of the 6th ACM Symposium on Information, Computer and Communications Security (CCS) (2011)
[5]
Castellanos, J.H., Ochoa, M., Zhou, J.: Finding dependencies between cyber-physical domains for security testing of industrial control systems. In: Proceedings of the 34th Annual Computer Security Applications Conference (ACSAC) (2018)
[6]
Etigowni, S., Hossain-McKenzie, S., Kazerooni, M., Davis, K., Zonouz, S.: Crystal (ball): I look at physics and predict control flow! just-ahead-of-time controller recovery. In: Proceedings of the 34th Annual Computer Security Applications Conference (ACSAC) (2018)
[7]
Garulli, A., Paoletti, S., Vicino, A.: A survey on switched and piecewise affine system identification. In: IFAC Proceedings Volumes (2012)
[8]
Goebel R, Teel AR, and Sanfelice RG Hybrid Dynamical Systems: Modeling, Stability, and Robustness 2012 Princeton Princeton University Press
[9]
Goh J, Adepu S, Junejo KN, and Mathur A Havarneanu G, Setola R, Nassopoulos H, and Wolthusen S A dataset to support research in the design of secure water treatment systems Critical Information Infrastructures Security 2017 Cham Springer 88-99
[10]
Goh, J., Adepu, S., Tan, M., Shan, L.Z.: Anomaly detection in cyber physical systems using recurrent neural networks. In: 2017 IEEE 18th International Symposium on High Assurance Systems Engineering (HASE) (2017)
[11]
Henzinger TA Inan MK and Kurshan RP The theory of hybrid automata Verification of Digital and Hybrid Systems 2000 Heidelberg Springer 265-292
[12]
Krotofil M and Cárdenas AA Riis Nielson H and Gollmann D Resilience of process control systems to cyber-physical attacks Secure IT Systems 2013 Heidelberg Springer 166-182
[13]
Kwon, C., Liu, W., Hwang, I.: Security analysis for cyber-physical systems against stealthy deception attacks. In: American Control Conference (ACC) (2013)
[14]
Lin, Q., Adepu, S., Verwer, S., Mathur, A.: 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 (2018)
[15]
Ljung L Procházka A, Uhlíř J, Rayner PWJ, and Kingsbury NG System identification Signal Analysis and Prediction 1998 Boston Springer 163-173
[16]
Murguia, C., van de Wouw, N., Ruths, J.: Reachable sets of hidden CPS sensor attacks: analysis and synthesis tools. IFAC-PapersOnLine (2017)
[17]
Pasqualetti F, Dörfler F, and Bullo F Attack detection and identification in cyber-physical systems IEEE Trans. Autom. Control 2013 58 2715-2729
[18]
Raffelt H and Steffen B Baresi L and Heckel R LearnLib: a library for automata learning and experimentation Fundamental Approaches to Software Engineering 2006 Heidelberg Springer 377-380
[19]
Santana, P.H., Lane, S., Timmons, E., Williams, B.C., Forster, C.: Learning hybrid models with guarded transitions. In: Conference on Artificial Intelligence (2015)
[20]
Teixeira, A., Amin, S., Sandberg, H., Johansson, K.H., Sastry, S.S.: Cyber security analysis of state estimators in electric power systems. In: 49th IEEE Conference on Decision and Control (CDC) (2010)
[21]
Urbina, D.I., et al.: Limiting the impact of stealthy attacks on industrial control systems. In: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security (CCS) (2016)
[22]
Van Der Schaft AJ and Schumacher JM An Introduction to Hybrid Dynamical Systems 2000 London Springer
[23]
Zimmerschied, R., Isermann, R.: Nonlinear system identification of block-oriented systems using local affine models. In: IFAC Proceedings Volumes (2009)
Recommendations
A Tale of Two Testbeds: A Comparative Study of Attack Detection Techniques in CPS
Critical Information Infrastructures SecurityAbstractAttack detection in cyber-physical systems (CPS) has been approached in several ways due to the complex interactions among the physical and cyber components. A comprehensive study is presented in this paper to compare different attack detection ...
CPSS '22: 8th ACM Cyber-Physical System Security Workshop
ASIA CCS '22: Proceedings of the 2022 ACM on Asia Conference on Computer and Communications SecurityCyber-Physical Systems (CPS) consist of large-scale interconnected systems of heterogeneous components interacting with their physical environments. There exist a multitude of CPS devices and applications deployed to serve critical functions in our ...
Cross-Domain Noise Impact Evaluation for Black Box Two-Level Control CPS
Special Issue on Dependability in CPSControl Cyber-Physical Systems (CPSs) constitute a major category of CPS. In control CPSs, in addition to the well-studied noises within the physical subsystem, we are interested in evaluating the impact of cross-domain noise: the noise that comes from ...
Comments
Information & Contributors
Information
Published In
Jun 2019
600 pages
ISBN:978-3-030-21567-5
DOI:10.1007/978-3-030-21568-2
© Springer Nature Switzerland AG 2019.
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 05 June 2019
Author Tags
Qualifiers
- Article
Contributors
Other Metrics
Bibliometrics & Citations
Bibliometrics
Article Metrics
- 0Total Citations
- 0Total Downloads
- Downloads (Last 12 months)0
- Downloads (Last 6 weeks)0
Reflects downloads up to 13 Nov 2024
Other Metrics
Citations
View Options
View options
Get Access
Login options
Check if you have access through your login credentials or your institution to get full access on this article.
Sign in