The Black Swan: The Impact of the Highly Improbable

At the core of the analysis task in the development process is information systems requirements modelling. Modelling of requirements has been occurring for many years and the techniques used have progressed from flowcharting through data flow diagrams and entity-relationship diagrams to object-oriented schemas today. Unfortunately, researchers have been able to give little theoretical guidance only to practitioners on which techniques to use and when. In an attempt to address this situation, Wand and Weber have developed a series of models based on the ontological theory of Mario Bunge—the Bunge–Wand–Weber (BWW) models. Two particular criticisms of the models have persisted however—the understandability of the constructs in the BWW models and the difficulty in applying the models to a modelling technique. This paper addresses these issues by presenting a meta model of the BWW constructs using a meta language that is familiar to many IS professionals, more specific than plain English text, but easier to understand than the set-theoretic language of the original BWW models. Such a meta model also facilitates the application of the BWW theory to other modelling techniques that have similar meta models defined. Moreover, this approach supports the identification of patterns of constructs that might be common across meta models for modelling techniques. Such findings are useful in extending and refining the BWW theory.

Developing a meta model for the Bunge–Wand–Weber ontological constructs

A method for risk modeling of interdependencies in critical infrastructures

Complex networks have been studied intensively for a decade, but research still focuses on the limited case of a single, non-interacting network. Modern systems are coupled together and therefore should be modelled as interdependent networks. A fundamental property of interdependent networks is that failure of nodes in one network may lead to failure of dependent nodes in other networks. This may happen recursively and can lead to a cascade of failures. In fact, a failure of a very small fraction of nodes in one network may lead to the complete fragmentation of a system of several interdependent networks. A dramatic real-world example of a cascade of failures (‘concurrent malfunction’) is the electrical blackout that affected much of Italy on 28 September 2003: the shutdown of power stations directly led to the failure of nodes in the Internet communication network, which in turn caused further breakdown of power stations. Here we develop a framework for understanding the robustness of interacting networks subject to such cascading failures. We present exact analytical solutions for the critical fraction of nodes that, on removal, will lead to a failure cascade and to a complete fragmentation of two interdependent networks. Surprisingly, a broader degree distribution increases the vulnerability of interdependent networks to random failure, which is opposite to how a single network behaves. Our findings highlight the need to consider interdependent network properties in designing robust networks.

http://absimage.aps.org/image/MAR10/MWS_MAR10-2009-001087.pdf

Catastrophic cascade of failures in interdependent networks

Data on lifeline system service restoration is seldom exploited for the calibration of performance prediction models or for response comparisons across systems and events. This study explores utili...

/pdf/quantification-of-lifeline-system-interdependencies-after-s3xe3f3n6m.pdf

Quantification of Lifeline System Interdependencies after the 27 February 2010 Mw 8.8 Offshore Maule, Chile, Earthquake

Safeguarding information intensive critical infrastructures against novel types of emerging failures

The paper explores the possibility of using interacting agents for modelling and discrete event simulation as a tool to approach interdependencies analysis and evaluation for critical infrastructures. A discrete event simulation system was developed, using agent-oriented programming, considering the following limited sets of critical infrastructures: a great hospital infrastructure, a railway transportation infrastructure and other public transportation infrastructures. Faults inside the electricity distribution system are simulated, producing electrical power outages whose duration could be variable with respect to time and space, and generating consequences inside the transportation infrastructures. The hospital infrastructure users, such as different types of physicians, nurses, subsidiary personnel, students and patients are also modelled using agent oriented architectures. The objective of the simulations is to study and analyse the interdependencies of the considered infrastructures Many typologies of test scenarios are also executed and the severity of the generated consequences are analysed in the paper.

Analysing interdependencies of critical infrastructures using agent discrete event simulation

This paper refers to research activities related to SAFEGUARD project (IST Project Number: IST-2001-32685). The aims of the project is to examine LCCI’s in terms of nature of different facets in each infrastructure: organizational, computational (cyber) and physical layers. Critical inter-dependencies among layers can thus be analyzed. Possible impact of bad events, early classified in attack scenarios with and without SAFEGUARD, will be coped with countermeasures to maintain at acceptable level system’s operability. SAFEGUARD, an agent-based middleware, is conceived to operate embedded inside of the cyber-layers, the more sensitive part to malicious attacks and anomalies, and is designed to enhance dependability and survivability of a LCCI. Self-healing mechanism of SAFEGUARD agents will start with the trouble diagnosis and classification using Hybrid Intrusion Detection techniques (software instrumentation, novelty detection, etc.). Once the problem has been diagnosed, a number of techniques will be used to solve and repair the fault (i.e.: adaptive middleware technology, backup, hot standby and so on). More self-healing mechanisms will have to be combined and coordinated to with an attempt to deal with the source of the problem.

Dependability and Survivability of Large Complex Critical Infrastructures

Risk assessment of urban areas aims at limiting the impact of harmful events by increasing awareness of their possible consequences. Qualitative risk assessment allows to figure out possible risk situations and to prioritize them, whereas quantitative risk assessment is devoted to measuring risks from data, in order to improve preparedness in case of crisis situations. We propose an automatic approach to comprehensive risk assessment. This leverages on a semantic and spatiotemporal representation of knowledge of the urban area and relies on a software system including: a knowledge base; two components for quantitative and qualitative risk assessments, respectively; and a WebGIS interface. The knowledge base consists of the TERMINUS domain ontology, to represent urban knowledge, and of a geo‐referenced database, including geographical, environmental and urban data as well as temporal data related to the levels of operation of city services. CIPcast DSS is the component devoted to quantitative risk assessment, and WS‐CREAM is the component supporting qualitative risk assessment based on computational creativity techniques. Two case studies concerning the city of Rome (Italy) show how this approach can be used in a real scenario for crisis preparedness. Finally, we discuss issues related to plausibility of risks and objectivity of their assessment.

A comprehensive system for semantic spatiotemporal assessment of risk in urban areas

When the complexity of a system increases, the number of possible faults and anomalous working conditions becomes very high; on the contrary, the number of 'normal' behaviours is generally low and often well determined by rules and constraints defined by the characteristics of the furnished services. In this paper, after a general overview of the SAFEGUARD system, a more detailed description of the agents, dedicated to early detection of anomalies and failures inside a Supervisory and Control and Data Acquisition (SCADA) system of an electricity transmission network is given. The paper also describes how it is possible to correlate the detected novelty events and to decide the right recovery policies avoiding inappropriate reactions caused by false alarms. A test benchmark of the novelty detection agents will be executed inside a simulated SCADA electricity transmission system and the layout of the utilised testing environment is described in the paper.

Giordano Vicoli

Papers

Safeguarding information intensive critical infrastructures against novel types of emerging failures

Analysing interdependencies of critical infrastructures using agent discrete event simulation

Dependability and Survivability of Large Complex Critical Infrastructures

A comprehensive system for semantic spatiotemporal assessment of risk in urban areas

Novelty detection and management to safeguard information-intensive critical infrastructures