Abstract
In manufacturing, concepts like the Internet of Things or Cyber-physical Systems accelerate the development from traditional production facilities towards smart factories. Thereby, emerging digital technologies increasingly connect information networks with production processes, forming complex smart factory networks (SFNs). Due to their reliance on information flows and the high degree of cross-linking, SFNs are, in particular, vulnerable to IT availability risks caused by attacks and errors. Against this backdrop, we present a modelling approach for analyzing the effects of IT threats on production processes. Based on Petri Nets, we provide modular SFN components for modelling SFN architectures and for simulating stochastic attack and error propagation. With this, we support the analysis and comparison of different SFN architectures regarding spreading effects, availability of information and production components, and associated effects on productivity. Our approach enables and serves as a foundation for decision support on SFN layouts from a risk perspective and the derivation of IT security mitigation measures in both research and practice. We evaluate our artefact by implementing and applying a software prototype in artificial and real-life settings.
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Data Availability
The datasets generated and analysed during the current study are available from the corresponding author on reasonable request.
Code Availability
The software prototype used during the current study is available in a public repository (https://www.dropbox.com/sh/sb1hjh5l1uczm6d/AAA1jECKT069lAxlvatYQI3ca?dl=0; GitHub upon acceptance).
Notes
https://www.dropbox.com/sh/sb1hjh5l1uczm6d/AAA1jECKT069lAxlvatYQI3ca?dl=0 [GitHub upon acceptance]
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Appendices
Appendix
Appendix B – Description of Artefact Instantiation as Software Prototype
We implemented an instantiation of our artefact as a software prototype in order to provide a proof of concept and evaluate its real-world fidelity and applicability by applying it in artificial and naturalistic settings. The software allows us to create different scenarios defining SFNs and simulate stochastic events and their impact on the availability of components. It was built using standard software development concepts and implemented using the numerical computing environment and programming language MATLAB, which is often chosen in scientific research due to its expressiveness and flexibility. We did not use traditional PN modelling software because there is no tool available that covers all used PN extensions and allows us to add additional functionality such as import and export of scenarios and static stochastic (Monte Carlo) simulation. Additionally, MATLAB offers high flexibility and reusability of components. Therefore, PNs are instantiated and manipulated in matrix notation, and the prototype uses built-in MATLAB functionality to simulate stochastic events. All modules of the implementation have been extensively tested to allow for robust, reproducible results. The simulation code can be accessed.Footnote 1
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Berger, S., van Dun, C. & Häckel, B. IT Availability Risks in Smart Factory Networks – Analyzing the Effects of IT Threats on Production Processes Using Petri Nets. Inf Syst Front (2022). https://doi.org/10.1007/s10796-022-10243-y
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DOI: https://doi.org/10.1007/s10796-022-10243-y
Keywords
- Smart factory network
- Information network
- Production network
- IT availability risks
- Attack propagation
- Petri nets