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On Practical Threat Scenario Testing in an Electric Power ICS Testbed
Industrial control system networks in real world usually require a complex composition of many different devices, protocols, and services. Unfortunately, such practical setups are rarely documented publicly in sufficient technical detail to allow third parties to use the system as reference for their research. As a result, security researchers often have to work with abstract and simplified system assumptions, which might not translate well to practice. In this work, we provide a comprehensive overview of the network services provided by industrial devices found in the EPIC (Electric Power and Intelligent Control) system at SUTD. We provide a detailed network topology of the different network segments, enumerate hosts, models, protocols, and services provided. We argue that such a detailed system description can serve as an enabler for more practical security research. In particular, we discuss how the reported information can be used for emulating a diverse set of important threat scenarios in the smart grid domain. In addition, the provided details allow other researchers to build more detailed models or simulations.
- Advanced Digital Sciences Center Singapore
- Agency for Science, Technology and Research Singapore
- Agency for Science, Technology and Research Singapore
- Singapore University of Technology and Design Singapore
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).20 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%
