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SecTwin 5.0

Cybersecurity Platform based on Digital Twins for Industry 5.0

Project Overview: 

SecTwin 5.0 is an R&D project established under the general conceptualization of Industry 5.0, with the sole mission of designing and developing a Cybersecurity Platform for Digital Twins, corresponding to the fifth industrial revolution[1];. The platform must ensure the integration of services and cybersecurity mechanisms, favoring the interaction of human processes, infrastructures and other Digital Twins.

More specifically, NICS Lab will provide for SecTwin 5.0 a framework for integrating the various security services and systems of the platform, as well as interfaces with all entities and actors involved. Security services will provide various essential protection components. At the same time, various support systems will be established on top of these services to enable 1) resilience for sustainable protection based on automatic decision making, self-learning and constant feedback[2]; 2) physical protection (“safety”) through the system’s own protection against possible cyber-attacks, such as advanced and persistent attacks; and 3) sustainability in terms of computational cost and energy consumption required by the services and support systems of the platform itself. 

Thus, the main objective of SecTwin 5.0 is to prevent/react against failures and improve resilience, not only to reduce the impact of cyber-attacks on our industry, but also to increase security, privacy[3] and trust among the various stakeholders.


Proyecto TED2021-129830B-I00 financiado por:


  1. Cristina Alcaraz and Javier Lopez (2023): Protecting Digital Twin Networks for 6G-enabled Industry 5.0 Ecosystems. In: IEEE Network Magazine, vol. 37, no. 2, pp. 302-308, 2023, ISSN: 0890-8044.
  2. Alberto Garcia and Cristina Alcaraz and Javier Lopez (2023): MAS para la convergencia de opiniones y detección de anomalías en sistemas ciberfísicos distribuidos. In: VIII Jornadas Nacionales de Investigación en Ciberseguridad (JNIC), Vigo, Forthcoming.
  3. Daniel Morales and Isaac Agudo and Javier Lopez (2023): Private set intersection: A systematic literature review. In: Computer Science Review, vol. 49, no. 100567, 2023, ISSN: 1574-0137.

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