Roberto Setola

Modelling interdependent infrastructures using interacting dynamical models

We investigate the consequence of failures, occurring on the electrical grid, on a telecommunication network. We have focused on the Italian electrical transmission network and the backbone of the internet network for research (GARR). Electrical network has been simulated using the DC power flow method; data traffic on GARR by a model of the TCP/IP basic features. The status of GARR nodes has been related to the power level of the (geographically) neighbouring electrical nodes (if the power level of a node is lower than a threshold, all communication nodes depending on it are switched off). The electrical network has been perturbed by lines removal: the consequent re-dispatching reduces the power level in all nodes. This reduces the number of active GARR nodes and, thus, its Quality of Service (QoS). Averaging over many configurations of perturbed electrical network, we have correlated the degradation of the electrical network with that of the communication network. Results point to a sizeable amplification of the effects of faults on the electrical network on the communication network, also in the case of a moderate coupling between the two networks.

Critical infrastructure dependency assessment using the input–output inoperability model

Abstract The input–output inoperability model (IIM) is a simple, but powerful, mechanism for analyzing the cascading effects induced by critical infrastructure dependencies and interdependencies. IIM typically uses financial data as a measure of the dependency phenomena. Since financial data is only one of the many dimensions for analyzing dependency phenomena, the quality of IIM parameters and, thus, the reliability of IIM results can be affected negatively. This paper proposes a methodology for evaluating IIM parameters based on technical and operational data. The data is collected by interviewing experts and is processed using a fuzzy set based methodology. A case study involving Italian critical infrastructure sectors is used to demonstrate the effectiveness of the methodology.

Agent-based input–output interdependency model

The modeling and analysis of critical infrastructures and their interdependencies are essential to discovering hidden vulnerabilities and the related threats to national and international security. Over the past few years, several approaches have been proposed to address this problem. The so-called holistic approaches are relatively abstract, but are easily validated using real economic data. Other approaches based on agent-based models provide deeper views of the interdependencies existing between subsystems of different infrastructures. However, agent-based models are often difficult to validate because quantitative data of the appropriate granularity may not be available. This paper presents an agent-based input–output inoperability model designed to overcome the limitations of the holistic and agent-based paradigms. In order to provide a detailed and expressive framework, the exchange of resources between infrastructures is explicitly modeled while inoperability becomes an internal parameter. Nevertheless, the model is easily transformed into a fine-grained, input–output inoperability model whose coefficients can be obtained based on real data.

Vulnerability modeling and analysis for critical infrastructure protection applications

Abstract Effective critical infrastructure protection requires methodologies and tools for the automated evaluation of the vulnerabilities of assets and the efficacy of protection systems. This paper presents a modeling language for vulnerability analysis in critical infrastructure protection applications. The language extends the popular Unified Modeling Language (UML) to provide vulnerability and protection modeling functionality. The extended language provides an abstract representation of concepts and activities in the infrastructure protection domain that enables model-to-model transformations for analysis purposes. The application of the language is demonstrated through a use case that models vulnerabilities and physical protection systems in a railway station.

Fuzzy dynamic input–output inoperability model

Abstract This paper describes an extension of the input–output inoperability model (IIM) that accommodates uncertain and vague data. In the resulting “fuzzy version” of the dynamic IIM model (FD-IIM), the level of inoperability of each infrastructure and the Leontief coefficients are specified using fuzzy variables that express expert knowledge about infrastructure interdependences. An important result is that, under certain conditions, solution convergence for the fuzzy model can be inferred based on the stability properties of the “crisp” (non-fuzzy) version of the system of interest. A case study involving the Italian critical infrastructure is used to demonstrate the feasibility and utility of the approach.

Improving Resilience of Interdependent Critical Infrastructures via an On-Line Alerting System

This paper illustrates the activities under development within the FP7 EU MICIE project. The project is devotedto design and implement an on-line alerting system, able toevaluate, in real time, the level of risk of interdependent Critical Infrastructures (CIs). Such a risk is generated by undesired events and by the high level of interconnection of the different infrastructures. Heterogeneous models are under development to perform short term predictions of the Quality of Service (QoS) of each CI according to the QoS of the others, to the level of interdependency among the Infrastructures, and according to the undesired events identified in the reference scenario.

Modelling critical infrastructure via a mixed holistic reductionistic approach

Infrastructure systems and their interaction mechanisms can be interpreted following a multitude of different approaches, depending on different perspectives and levels of abstraction. In this paper, we propose a mixed approach, in which different representations of the same infrastructure is used in order to define the interdependencies and interactions among infrastructures and their elements. We explicitly introduce into our model the three concepts of: infrastructure, component and interaction; and model, on one hand, intra-domain dependencies with a reductionistic approach and, on the other hand, inter-domain dependencies mainly using a holistic vision.

Distributed synchronization under uncertainty: A fuzzy approach

In this paper the synchronization of a network of identical systems with fuzzy initial conditions is introduced, as a convenient framework to obtain a shared estimation of the state of a system based on partial and distributed observations, in the case where such a state is affected by ambiguity and/or vagueness. After discussing the synchronization of crisp systems, providing a criteria to find the information sharing law that lets the network converge to a shared trajectory, Discrete-Time Fuzzy Systems (DFSs) are introduced as an extension of scalar fuzzy difference equations. Besides providing a stability condition for a general DFS, in the linear case it is proven that, under a non-negativity assumption for the coefficients of the system, the fuzzyfication of the initial conditions does not compromise the stability of the crisp system. A framework for the synchronization of arrays of linear DFS is then introduced, proving that the crisp synchronization is a particular case of the proposed approach. Finally, a case study in the field of Critical Infrastructure Protection is provided.

Proteins as Networks: A Mesoscopic Approach Using Haemoglobin Molecule as Case Study

Protein structures allow for a straightforward representation in terms of graph theory being the nodes the aminoacid residues and the edges the scoring of a spatial contact between the node pairs. Such a representation allows for a direct use in the realm of protein science of the vast repertoire of graph invariants developed in the analysis of complex networks. In this work we give a general overview of the protein as networks paradigm with a special emphasis on haemoglobin where the most important features of protein systems like allostery, protein-protein contacts and differential effect of mutations were demonstrated to be amenable to a graph theory oriented translation.

An Integrated Approach For Simulating Interdependencies

The detailed simulation of interdependent critical infrastructures is a hard problem. Major challenges include modeling multiple heterogeneous infrastructures in a single framework and expressing internal dependencies and interdependencies between infrastructures. This paper attempts to address these issues by proposing a simulation framework where several sector-specific simulators (vertical simulators) are integrated into a general simulation environment (horizontal simulator). Specialized software implemented in the vertical simulators models individual infrastructures and their intra-domain dynamics. The horizontal simulator effectively captures inter-domain relationships and merges heterogeneous information from the vertical simulators to facilitate comprehensive infrastructure simulations.