Papers & Presentations

Economic well-being and our social fabric are tightly linked to lifeline technological systems. They are electric power, gas pipelines, telecommunications, transportation, waste disposal and water supply. During disasters, those systems must, at least, quickly return to an acceptable level of service to allow a fast emergency management in terms of rescue of injured people and preservation of health one. Furthermore, such systems involve physical and electronic networks that are interdependent within and across multiple domains, causing unpredictable consequences during adverse events and restoration process. Therefore, it is mandatory to understand overall risks that disasters pose to lifeline systems to rightly recover from such situations. In this paper, two decision support systems are presented. The first is an emergency console where several damaged infrastructures are analyzed in order to decide the kind of interventions in terms of personnel, carriers and places. The second is an electrical demand/response console deployed in a power control room where a smart grid is dynamically configured by the startup/shutdown of generator sources. The decision support systems are based upon with the output of CISIApro tool, an agent-based simulator for evaluating risk of interdependent systems. This system has been validated within the European URANIUM CIPS project by means of a realistic and quite complex reference scenario made of four interconnected infrastructures in a regional area. System output is visualized through a synoptic web-based view of predicted situations and suggested procedures.

Dependencies and interdependencies between critical infrastructures are difficult to identify and model because their effects appear infrequently with unpredictable consequences. The addition of cyber attacks in this context makes the analysis even more complex. Integrating the consequences of cyber attacks and interdependencies requires detailed knowledge about both concepts at a common level of abstraction. CISIApro is a critical infrastructure simulator that was created to evaluate the consequences of faults and failures in interdependent infrastructures. This chapter demonstrates the use of CISIApro to evaluate the effects of cyber attacks on physical equipment and infrastructure services. A complex environment involving three interconnected infrastructures is considered: a medium voltage power grid managed by a control center over a SCADA network that is interconnected with a general-purpose telecommunications network. The functionality of the simulator is showcased by subjecting the interconnected infrastructures to an ARP spoofing attack and worm infection. The simulation demonstrates the utility of CISIApro in supporting decision making by electric grid operators, in particular, helping choose between alternative fault isolation and system restoration procedures.

The increasing exploitation of the internet leads to new uncertainties, due to interdependencies and links between cyber and physical layers. As an example, the integration between telecommunication and physical processes, that happens when the power grid is managed and controlled, yields to epistemic uncertainty. Managing this uncertainty is possible using specific frameworks, usually coming from fuzzy theory such as Evidence Theory. This approach is attractive due to its flexibility in managing uncertainty by means of simple rule-based systems with data coming from heterogeneous sources. In this paper, Evidence Theory is applied in order to evaluate risk. Therefore, the authors propose a frame of discernment with a specific property among the elements based on a graph representation. This relationship leads to a smaller power set (called Reduced Power Set) that can be used as the classical power set, when the most common combination rules, such as Dempster or Smets, are applied. The paper demonstrates how the use of the Reduced Power Set yields to more efficient algorithms for combining evidences and to application of Evidence Theory for assessing risk.

In the last ten years, the emergency response has been a key point for the welfare of citizens as well as for the economic losses. The widespread technology deployment improves the emergency response but the existing interdependencies among physical and cyber systems generate unpredictable consequences in the reconfiguration procedures. Our solution aims to provide a timely and an efficient tool for decision support that is simple to use also in complex emergency scenarios. This system gathers data from several SCADA (Supervisory Control and Data Acquisition) systems of Critical Infrastructures (CIs), such as power grid, gas and pipelines, telecommunication network, and transportation. The core of this solution is two cascading modules: the first is CISIApro tool for evaluating risk of interdependent CIs and the second is an expert system for managing civil protection operations. CISIApro tool fuses data and information coming from SCADA systems in order to understand the consequences of negative events, such as faults, natural disasters and cyber-attacks. CISIApro models infrastructures and their interdependencies using an agent-based technique where each agent evaluates its own risk using information coming from its neighborhood. The expert system is based on structured decision support methodologies. It provides a suggestion for managing and optimizing the intervention procedures of civil protection. The output of this process is a cockpit, i.e., a synoptic view of predicted situations and a suggestion for emergency procedures. This approach is experimented and under test on a realistic and quite complex case study of a smart area. The efficiency of emergency procedures is shown to be improved in terms of cost and time by means of a semi-automatic process where decision makers are needed.

In the last ten years, the emergency response has been a key point for the welfare of citizens as well as for the economic losses. The widespread technology deployment improves the emergency response but the existing interdependencies among physical and cyber systems generate unpredictable consequences in the reconfiguration procedures. The European project URANIUM aims to provide a timely and an efficient tool for decision support that is simple to use also in complex emergency scenarios. This system gathers data from several SCADA (Supervisory Control and Data Acquisition) systems of Critical Infrastructures (CIs), such as power grid, gas and pipelines, telecommunication network, and transportation. The core of URANIUM project is two cascading modules: the first is CISIApro tool for evaluating risk of interdependent CIs and the second is an expert system for managing civil protection operations. CISIApro tool fuses data and information coming from SCADA systems in order to understand the consequences of negative events, such as faults, natural disasters and cyber-attacks. CISIApro models infrastructures and their interdependencies using an agent-based technique where each agent evaluates its own risk using information coming from its neighborhood. The expert system is based on structured decision support methodologies. It provides a suggestion for managing and optimizing the intervention procedures of civil protection. The output of this process is a cockpit, i.e., a synoptic view of predicted situations and a suggestion for emergency procedures. This approach is experimented and under test on a realistic and quite complex case study of a smart area. The efficiency of emergency procedures is shown to be improved in terms of cost and time by means of a semi-automatic process where decision makers are needed.