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C. Alcaraz, and J. Lopez, "Digital Twin: A Comprehensive Survey of Security Threats",
IEEE Communications Surveys & Tutorials, vol. 24, issue 3, no. thirdquarter 2022, IEEE, pp. 1475 - 1503, 04/2022. DOI (I.F.: 25.249)More..

Abstract

Industry 4.0 is having an increasingly positive impact on the value chain by modernizing and optimizing the production and distribution processes. In this streamline, the digital twin (DT) is one of the most cutting-edge technologies of Industry 4.0, providing simulation capabilities to forecast, optimize and estimate states and configurations. In turn, these technological capabilities are encouraging industrial stakeholders to invest in the new paradigm, though an increased focus on the risks involved is really needed. More precisely, the deployment of a DT is based on the composition of technologies such as cyber-physical systems, the Industrial Internet of Things, edge computing, virtualization infrastructures, artificial intelligence and big data. However, the confluence of all these technologies and the implicit interaction with the physical counterpart of the DT in the real world generate multiple security threats that have not yet been sufficiently studied. In that context, this paper analyzes the current state of the DT paradigm and classifies the potential threats associated with it, taking into consideration its functionality layers and the operational requirements in order to achieve a more complete and useful classification. We also provide a preliminary set of security recommendations and approaches that can help to ensure the appropriate and trustworthy use of a DT.

Impact Factor: 25.249
Journal Citation Reports® Science Edition (Thomson Reuters, 2020)

PDF icon Alcaraz2022b.pdf (1.26 MB)
S. Fischer-Hübner, et al., "Stakeholder Perspectives and Requirements on Cybersecurity in Europe",
Journal of Information Security and Applications, vol. 61, no. 102916, Elsevier, 09/2021. DOI (I.F.: 3.872)More..
Impact Factor: 3.872
Journal Citation Reports® Science Edition (Thomson Reuters, 2020)

PDF icon Alcaraz2021a.pdf (507.76 KB)
A. Nieto, A. Acien, and G. Fernandez, "Crowdsourcing analysis in 5G IoT: Cybersecurity Threats and Mitigation",
Mobile Networks and Applications (MONET), Springer US, pp. 881-889, 10/2018. DOI (I.F.: 2.39)More..

Abstract

Crowdsourcing can be a powerful weapon against cyberattacks in 5G networks. In this paper we analyse this idea in detail, starting from the use cases in crowdsourcing focused on security, and highlighting those areas of a 5G ecosystem where crowdsourcing could be used to mitigate local and remote attacks, as well as to discourage criminal activities and cybercriminal behaviour. We pay particular attention to the capillary network, where an infinite number of IoT objects coexist. The analysis is made considering the different participants in a 5G IoT ecosystem.

Impact Factor: 2.39
Journal Citation Reports® Science Edition (Thomson Reuters, 2018)

PDF icon NAFMONET2018.pdf (1.04 MB)
J. L. Hernández-Ardieta, et al., "An Intelligent and Adaptive Live Simulator: A new Concept for Cybersecurity Training",
9th Future Security Conference, 2014. More..

Abstract

The rapid rate of change in technology and the increasing sophistication of cyber attacks require any organization to have a continuous preparation. However, the resource and time intensive nature of cybersecurity education and training renders traditional approaches highly inefficient. Simulators have attracted the attention in the last years as a potential solution for cybersecurity training. However, in spite of the advances achieved, there is still an urgent need to address some open challenges. In this paper we present a novel simulator that solves some these challenges. First, we analyse the main properties that any cybersecurity training solution should comprise, and evaluate to what extent training simulators can meet them. Next, we introduce the functional architecture and innovative features of the simulator, of which a functional prototype has already been released. Finally, we demonstrate how these capabilities are put into practice in training courses already available in the simulator.

PDF icon 1637.pdf (1005.4 KB)
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