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Risk and resilience assessment and improvement in the telecommunication industry

: Fehling-Kaschek, Mirjam; Miller, Natalie; Haab, Gael; Faist, Katja; Stolz, Alexander; Häring, Ivo; Neri, Alberto; Celozzi, Giuseppe; Sanchez, Jose; Valera, Javier; Makri, Rodoula

Fulltext ()

Baraldi, P.:
30th European Safety and Reliability Conference and 15th Probabilistic Safety Assessment and Management Conference, ESREL/PSAM 2020. E-Proceedings. Online resource : 01 - 06 November 2020, Venice, Italy
Singapore: Research Publishing, 2020
ISBN: 978-981-14-8593-0
8 pp.
European Safety and Reliability Conference (ESREL) <30, 2020, Online>
Probabilistic Safety Assessment and Management Conference (PSAM) <15, 2020, Online>
European Commission EC
H2020; 786409; RESISTO
Conference Paper, Electronic Publication
Fraunhofer EMI ()
resilience quantification; telecommunication; critical infrastructure; network simulation

A growing number of consumer and industrial functionalities, including safety relevant and safety critical functions and services, rely on reliable and resilient telecommunication infrastructures. As telecommunication grids advance virtualization, are designed resembling the internet and are moving towards 5G, the interest to quantify their resilience with respect to major disruptions is increasing. Due to this increasing complexity of the telecom infrastructures, as attack types and often intensities are growing, their potential susceptibility and vulnerability increases. In this context, the main goal of the EU-funded H2020 project RESISTO is to provide an innovative solution for the cyber-physical resilience enhancement and holistic situation awareness for communication infrastructures. The solution consists of two main parts, the short term and the long-term components. While the short term components are designed to respond to events in real time and provide a decision support system, the long term components, mainly described herein, feature a risk and resilience analysis, based on a holistic risk and resilience management process created in previous work. Based on the inputs and a simulation grid approach, first results on the resilience quantification are presented resorting to graphical analyses and distributions for behavioral modeling. Finally, the integration of the long-term tool in the RESISTO solution and its interaction with the short term components is discussed.