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Computers & Security
Article . 2025 . Peer-reviewed
License: CC BY
Data sources: Crossref
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https://doi.org/10.2139/ssrn.4...
Article . 2024 . Peer-reviewed
Data sources: Crossref
DBLP
Article . 2025
Data sources: DBLP
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Scass: Breaking into Scada Systems Security

Authors: Nicola d'Ambrosio; Giulio Capodagli; Gaetano Perrone; Simon Pietro Romano;

Scass: Breaking into Scada Systems Security

Abstract

Industrial Controls Systems (ICS) represent a relevant target for attackers. In order to prevent such critical security threats, ICS security assessment activities should be conducted. Conventional vulnerability assessment and penetration testing within ICSs are not practicable due to safety risks and cost constraints. To overcome these challenges, security researchers have developed cybersecurity testbeds. However, these testbeds commonly rely on closed components, cannot be extended, and are very expensive. This research investigates how a modular, open-source framework can enhance the development of robust cybersecurity testbeds and facilitate the implementation of digital twins for securing Industrial Control Systems. We present SCASS, a fully customizable testbed designed to replicate complex SCADA and ICS environments with high fidelity. SCASS addresses the need for accessible, scalable platforms by supporting both physical and virtual components while enabling the evaluation of heterogeneous attack scenarios and security methodologies. By combining advanced attack scenarios with an objective comparative analysis against existing testbeds, SCASS demonstrates its ability to fill critical gaps in the ICS security landscape, fostering collaboration and advancing security assessment methodologies.

Country
Italy
Related Organizations
Keywords

ICS cyber-ranges; ICS cybersecurity; ICS testbeds; SCADA systems, ICS cyber-ranges, ICS cybersecurity, ICS testbeds, SCADA systems

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    selected citations
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    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).
    8
    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).
    Average
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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selected citations
These citations are derived from selected sources.
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).
BIP!Citations provided by BIP!
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.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Top 10%
Green
hybrid