Welfare in developed countries strongly relies on many heterogeneous infrastructures generically named as critical infrastructures. These infrastructures, designed as autonomous systems, are actually more and more mutually dependent. This introduces new and extremely dangerous vulnerabilities in the overall system because an accidental or a malicious fault (e.g. terroristic attack) could exploit these "connections" to unpredictably spread, amplifying its negative consequences and affecting unforeseeable and haphazard sets of users. In this paper, we analyse performance degradation induced on this system of systems by the presence and spreading of failures in order to emphasise the most critical links existing among different phenomena. Due to uncertainties that characterise these systems, we use Fuzzy Numbers (FNs) to represent involved quantities. This allows a modelling approach that can be set up using also qualitative information that are easier to obtain from experts and stakeholders. Moreover, this choice brings to a better characterisation of the level of confidence of our results. Preliminary results on a simple case study illustrate the effectiveness of the proposed approach.
DE PORCELLINIS, S., Panzieri, S., Setola, R., Ulivi, G. (2008). Failures Propagation in Critical Interdependent Infrastructures. INTERNATIONAL JOURNAL OF MODELLING, IDENTIFICATION AND CONTROL, 3 (1), 69-78 [10.1504/IJMIC.2008.018186].
Failures Propagation in Critical Interdependent Infrastructures
PANZIERI, Stefano;G. ULIVI
2008-01-01
Abstract
Welfare in developed countries strongly relies on many heterogeneous infrastructures generically named as critical infrastructures. These infrastructures, designed as autonomous systems, are actually more and more mutually dependent. This introduces new and extremely dangerous vulnerabilities in the overall system because an accidental or a malicious fault (e.g. terroristic attack) could exploit these "connections" to unpredictably spread, amplifying its negative consequences and affecting unforeseeable and haphazard sets of users. In this paper, we analyse performance degradation induced on this system of systems by the presence and spreading of failures in order to emphasise the most critical links existing among different phenomena. Due to uncertainties that characterise these systems, we use Fuzzy Numbers (FNs) to represent involved quantities. This allows a modelling approach that can be set up using also qualitative information that are easier to obtain from experts and stakeholders. Moreover, this choice brings to a better characterisation of the level of confidence of our results. Preliminary results on a simple case study illustrate the effectiveness of the proposed approach.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.