Complex Critical Infrastructures Research Articles

Human factors and cyber-security risks on the railway – the critical role played by signalling operations

PurposeRailways are a well-known example of complex critical infrastructure, incorporating socio-technical systems with humans such as drivers, signallers, maintainers and passengers at the core. The technological evolution including interconnectedness and new ways of interaction lead to new security and safety risks that can be realised, both in terms of human error, and malicious and non-malicious behaviour. This study aims to identify the human factors (HF) and cyber-security risks relating to the role of signallers on the railways and explores strategies for the improvement of “Digital Resilience” – for the concept of a resilient railway.Design/methodology/approachOverall, 26 interviews were conducted with 21 participants from industry and academia.FindingsThe results showed that due to increased automation, both cyber-related threats and human error can impact signallers’ day-to-day operations – directly or indirectly (e.g. workload and safety-critical communications) – which could disrupt the railway services and potentially lead to safety-related catastrophic consequences. This study identifies cyber-related problems, including external threats; engineers not considering the human element in designs when specifying security controls; lack of security awareness among the rail industry; training gaps; organisational issues; and many unknown “unknowns”.Originality/valueThe authors discuss socio-technical principles through a hexagonal socio-technical framework and training needs analysis to mitigate against cyber-security issues and identify the predictive training needs of the signallers. This is supported by a systematic approach which considers both, safety and security factors, rather than waiting to learn from a cyber-attack retrospectively.

Transforming the grid for a more environmentally and socially sustainable electricity system in Great Britain is a slow and uneven process.

Electricity system decarbonization is key for environmental sustainability. From a consumption-production perspective, much attention has been paid to changes in how electricity is generated and used, but electricity systems also rely on a grid infrastructure that connects and integrates production and consumption, and which will also need to transform. At the same time, new technologies in the electricity system, including the grid, offer the potential for more socially sustainable ways of producing and consuming energy. However, in practice, change has been slow, uneven, and often dysfunctional. A socio-technical transitions approach offers insights into why this is so, seeing electricity system change not simply in technical and economic terms, but also as the outcomes of interactions between technology and social and political processes. The approach draws attention to the particular challenges of achieving rapid transitions in complex critical infrastructures like electricity with strong institutional logics of security. This article applies this approach to the case of Great Britain, where despite strong commitments to sustainability in the form of high-level climate policy, the electricity grid has often been a constraint on the pace of change. The nature of the British transition is explained partly by weak links between these high-level goals on the one hand and the detailed rules and practices in the electricity system on the other. It is also explained by patterns of ownership and grid regulation in the British case that protect incumbents and make it difficult for new actors to develop the system in more socially sustainable directions.

LiDiTE: A Full-Fledged and Featherweight Digital Twin Framework

The rising of the Cyber-Physical System (CPS) and the Industry 4.0 paradigms demands the design and implementation of Digital Twin Frameworks (DTFs) that may support the quick build of reliable Digital Twins (DTs) for experimental and testing purposes. Most of the current DTF proposals allow the generation of DTs at a good pace but affect generality, scalability, portability, and completeness. As a consequence, current DTF are mostly domain-specific and hardly span several application domains (e.g., from simple IoT deployments to the modeling of complex critical infrastructures). Furthermore, the generated DTs often requires a high amount of computational resource to run. In this paper, we present LiDiTE, a solution based on a novel reference model for general-purpose DTFs. LiDiTE overcomes the limitations of state-of-the-art tools by supporting the fine-grained development of real-world complexity scenarios. To achieve that, LiDiTE builds on technologies that favor scalability, reuse, and extensibility of scenarios. We show such features by building the DT of real critical infrastructure and evaluating the performance of our DT against those of the real system. Further contributions of this paper include open access to the source code of LiDiTE and the experimental dataset.

The Importance of Resistance in the Context of Critical Infrastructure Resilience: An Extension of the CIERA Method

Technical sectors compose an inseparable and elementary part of a complex critical infrastructure (CI) system. Their provided services are essential to the functioning of all of the dependent sectors of CI on which society and states depend, especially in areas experiencing high levels of urbanisation. The initial point for effective CI elements’ protection is the permanent assessment and strengthening of their capacity for resilience to the negative effects of internal and external threats. The current perceptions of resilience focus primarily on repressive components responsive to incidents (i.e., robustness, recoverability, and adaptability), while minimal attention is paid to the preventative components. The article’s contribution to this literature gap is its definition of resistance, which can be considered as a CI element’s ability to prevent the occurrence of incidents. To this goal, the current study defines (1) the individual factors (variables and parameters) determining CI resistance and (2) the methodological procedure for infrastructure element resistance assessment in order to identify the weak points throughout a complex CI system and subsequently strengthen them. Moreover, a practical example of resistance assessment for a selected critical energy infrastructure element is presented. The main outcome of this article is the definition of the primary steps for the expansion of the CIERA method, via the enhancement of CI components’ resilience capacity in the prevention phase.

An innovative framework for risk assessment of non-structural components for industrial plants

Na-Tech events (Natural Hazard Triggering Technological Disasters) are industrial accidents triggered by natural events such as hurricanes, floods, earthquakes, tsunami, etc. In the recent decades, various analytical approaches for the performance-based earthquake engineering (PBEE) have been developed. The most famous approach has been provided by the Pacific Earthquake Engineering Research (PEER) Center, which consists of four stages: hazard analysis, demand analysis, damage analysis, and risk assessment. The accuracy of this method in the case of complex critical infrastructure, such as nuclear and non-nuclear industrial plants, is still under investigation. Specifically for these critical structures, it is necessary to define different Limit States and appropriate Engineering Demand Parameters (EDP), especially in presence of critical Non-Structural Components (NSC), whose damage can have serious consequences. Furthermore, because of the narrow distribution of frequencies in the demand of NSC, the selection of ground motion records for fragility analysis is also a critical aspect. Consequently, the aim of the proposed study is to investigate the suitability of the PBEE approach in presence of NSCs and their dynamic interaction with the primary structure. On these premises, a comprehensive shake table test campaign was carried out with the aim to investigate the seismic behaviour of two structural configurations of a representative industrial multi-storey frame equipped with process NSCs. The main limit states for NCSs are identified and the related fragility curves are built, in a PBEE perspective, based on both experimental results and finite element model (FEM) simulations. For this purpose, an innovative algorithm for ground accelerogram selection is used. Finally, the mean annual frequency (MAF) of exceedance of the experimentally identified limit states for relevant NSCs is carried out.

ANALYSIS OF CYBER RESISTANCE ASSESSMENT METHODS OF CRITICAL INFRASTRUCTURE

The availability of critical infrastructure through cyberspace makes national security dependent on the degree of its security. Critical infrastructure is a set of automated management systems, which provide the interaction of information and telecommunications networks that solve problems of public administration, defense, security and law enforcement, and others. The protection of critical infrastructure directly depends on the possession of the relevant structures of new weapons, the degree of its effectiveness, methods of use and means of protection against the same weapons of the enemy. It is necessary to address the issue of effective confrontation in cyberspace. The analysis of problems in the development of methods for assessing the functional stability of critical infrastructure in cyber confrontation requires the definition of basic methods and criteria that can be used in Ukraine to assess the stability of critical infrastructure. Cyber weapons, which carry out destructive information effects, are not weapons in the classical sense, because they do not physically damage the object of attack, but translate its information and automated control systems into a crisis mode of operation. The process of counteraction of two or more parties, in this form, is a cyber confrontation that is realized using a common common resource - the global information space. In the process of critical infrastructure management, cyber confrontation imposes additional requirements to ensure the sustainable operation of critical infrastructure. Stability is an integral property that is inextricably linked to the operating environment. Cyber resilience is an integrated indicator and is determined by cyber reliability, which reflects the ability to perform its tasks in a complex critical infrastructure management system in the context of information destructive influences.

Geomatics and Soft Computing Methods for Infrastructure Monitoring

Our society is heavily dependent on many interdependent and complex critical infrastructures. Deficiencies in the functionality of the transportation network (e.g., vehicular traffic interruptions or limitations) can cause enormous inconvenience to communities and people. The Italian transport infrastructure heritage and new infrastructure construction is so relevant that the issue of its preservation and safety has become a priority. Specialistic advice is therefore required to understand if the static behaviour of these infrastructure has changed significantly after extraordinary events (e.g., earthquakes, landslides). With the advent of the internet of things (IoT), infrastructures are becoming smart and procedures simpler. In the framework of smart infrastructure development, we implemented an experimental system that integrates soft computing and geomatic methodologies for solving early warning problems. This system, which has been tested on the Petrace bridge (Southern Italy), is able to generate forecasting information on the infrastructure behaviour over time, mainly exploiting geomatic parameters. We built this "early warning/predictive" system through integration of several significant (geometric/structural) infrastructure models, which have been merged into a final "type" model. The results derived from various possible scenarios have been implemented in a neural network. The only system’s input is represented by displacement measurements acquired by sensors placed on the infrastructure, and the output consists in an estimation of different risk levels. Sensor data are then transmitted to a control unit that sends them to a processing server, where the calculation system is hosted. All received data and model results are displayed on the Wordpress platform with colour codes calibrated on the calculated risk thresholds.

Building Resilience and Recoverability of Electric Grid Communications

Industrialized society depends on continuously operating critical infrastructures, especially the electric grid and its associated telecommunications systems. A widespread, long‐term outage of grid systems can result from natural disasters, accidents, or intentional actions. When such an outage occurs, outside assistance may be unavailable or impractical. Resulting societal impacts can be severe—even deadly. Therefore, infrastructures should be designed for resilience to prevent collapse and to facilitate rapid recovery.The telecommunications system for the U.S. electric grid exemplifies a subsystem vulnerable to such a long‐term outage. An electromagnetic pulse (EMP) can cause such an outage to telecommunication systems. To ensure resilience to an EMP event, the equipment can be shielded and collocated with protected on‐site power and long‐duration fuel storage.Building resilience and facilitating reconstitution of the grid telecommunication system would have societal benefits far exceeding the investments required to obtain these capabilities. The cost estimation methodology we use in this analysis is broadly applicable for a variety of hazards and threats to complex critical infrastructures.

Critical Infrastructures Vulnerability and Risk Analysis

Vulnerability and risk analysis are considered in relation to critical infrastructures protection. The complexity of critical infrastructures is presented as a challenging characteristic, which calls for new approaches of analysis and the integration of different modeling perspectives. The concepts of vulnerability, risk and resilience are discussed in details and analyzed with respect to their characterization in critical infrastructures (CIs) and the challenges therein. Recent new perspectives on these concepts and their interpretations are also discussed in relation to their applicability for analyzing CI vulnerability and risk, in view of decision making for protection. Throughout the paper, reference is made to systems like the (smart) electric power grid and the Internet, to further exemplify the concepts and issues discussed.

Master Failure Detection Protocol in Internal Synchronization Environment

During the last decades, the wide advance in the networking technologies has allowed the development of distributed monitoring and control systems. These systems show advantages compared with centralized solutions: heterogeneous nodes can be easily integrated, new nodes can be easily added to the system, and no single point of failure. For these reasons, distributed systems have been adopted in different fields, such as industrial automation and telecommunication systems. Recently, due to technology improvements, distributed systems are also adopted in the control of power-grid and transport systems, i.e., the so-called large-scale complex critical infrastructures. Given the strict safety, security, reliability, and real-time requirements, using distributed systems for controlling such critical infrastructure demands that adequate mechanisms have to be established to share the same notion of time among the nodes. For this class of systems, a synchronization protocol, such as the IEEE 1588 standard, can be adopted. This type of synchronization protocol was designed to achieve very precise clock synchronization, but it may not be sufficient to ensure safety of the entire system. For example, instability of the local oscillator of a reference node, due to a failure of the node itself or to malicious attacks, could influence the quality of synchronization of all nodes. In recent years, a new software clock, the reliable and self-aware clock (R&SAClock), which is designed to estimate the quality of synchronization through statistical analysis, was developed and tested. This statistical instrument can be used to identify any anomalous conditions with respect to normal behavior. A careful analysis and classification of the main points of failure of IEEE 1588 standard suggests that the reference node, which is called master, is the weak point of the system. For this reason, this paper deals with the detection of faults of the reference node(s) of an of IEEE 1588 setup. This paper describes and evaluates the design of a protocol for timing failure detection for internal synchronization based on a revised version of the R&SAClock software suitably modified to cross-exploit the information on the quality of synchronization among all the nodes of the system. The experimental evaluation of this approach confirms the capability of the synchronization uncertainty, which is provided by R&SAClock, to reveal the anomalous behaviors either of the local node or of the reference node. In fact, it is shown that, through a proper configuration of the parameters of the protocol, the system is able to detect all the failures injected on the master in different experimental conditions and to correctly identify failures on slaves with a probability of 87%.

Simulation to Aid Disaster Planning and Mitigation: Tools and Techniques for Water Distribution Managers and Emergency Planners

AbstractCommunities depend on increasingly complex critical infrastructures to meet residents’ daily needs and to facilitate emergency response. The potential for cascading failures could intensify the consequences of disasters and complicate the process of planning for effective emergency response. This article presents a methodology for conducting a vulnerability analysis based on simulation of water distribution’s role in emergency response under various complex-disaster scenarios in which incapacity of the water system is coupled with an urban fire. The analysis reported here was run on a virtual (but detailed and realistic) small-town water distribution system to permit candid discussion of the insights derived from the vulnerability analysis and to avoid disclosing the vulnerabilities of a real system. The analysis methodology presented may be adapted to fit the needs of real communities. The results of these simulations are used to demonstrate a procedure for designing and testing mitigation method...

On data dissemination for large-scale complex critical infrastructures

Middleware plays a key role for the achievement of the mission of future large scale complex critical infrastructures, envisioned as federations of several heterogeneous systems over Internet. However, available approaches for data dissemination result still inadequate, since they are unable to scale and to jointly assure given QoS properties. In addition, the best-effort delivery strategy of Internet and the occurrence of node failures further exacerbate the correct and timely delivery of data, if the middleware is not equipped with means for tolerating such failures.This paper presents a peer-to-peer approach for resilient and scalable data dissemination over large-scale complex critical infrastructures. The approach is based on the adoption of epidemic dissemination algorithms between peer groups, combined with the semi-active replication of group leaders to tolerate failures and assure the resilient delivery of data, despite the increasing scale and heterogeneity of the federated system. The effectiveness of the approach is shown by means of extensive simulation experiments, based on Stochastic Activity Networks.

Architectural Evolution of Monitor and Control Systems - Issues and Challenges

Large-scale Complex Critical Infrastructures (LCCIs), such as power grids and transport infrastructures ( e.g. , network of airports and seaports), play a key role into several fundamental human activities, and represent the next generation of Monitor and Control Systems. They make extensive usage of Information and Communications Technology ( e.g. , computing systems, communication networks, and sensing hardware) for providing support for advanced monitoring and control facilities. However, solutions currently adopted in the field exhibit several inefficiencies when applied to LCCI. On the contrary, Distributed Event Based Systems (DEBS) seam promising solutions due to their intrinsic decoupling properties that enforce strong scalability degrees. However, they also present some open issues when dealing with the challenges imposed by LCCIs. This paper provides an introduction on LCCIs, a presentation of their challenges, and an analysis on the adoption of DEBS for LCCIs.

A dynamic Bayesian network based framework to evaluate cascading effects in a power grid

In recent years, the growing interest toward complex critical infrastructures and their interdependencies have solicited new efforts in the area of modeling and analysis of large interdependent systems. Cascading effects are a typical phenomenon of dependencies of components inside a system or among systems. The present paper deals with the modeling of cascading effects in a power grid. In particular, we propose to model such effects in the form of dynamic Bayesian networks (DBN) which can be derived by means of specific rules, from the power grid structure expressed in terms of series and parallel modules. In contrast with the available techniques, DBN offer a good trade-off between the analytical tractability and the representation of the propagation of the cascading event. A case study taken from the literature, is considered as running example.

Urban vulnerabilities: think simple

Noting the signals coming from the community of complex critical infrastructures management indicating, on the one hand, a definite preoccupation with identifying and properly characterising system vulnerabilities and, on the other hand, a dissatisfaction with (generally) expert capabilities to provide the effective ways and means sought, this paper submits that contributing to the situation is experts being caught in an unfortunate spiral of attempting to match objective complexity with increasingly complex, sometimes unintelligible for the stakeholders, solutions. It is suggested that an occasional change of lane in methodology, on the less analytical yet surprisingly insightful path lead by heuristic methods including cellular automata schemes may bring in just the breath of fresh air that may restore some degree of confidence in 'what nerds can usefully tell practitioners'.

Modeling Cascading Failure Propagation through Dynamic Bayesian Networks

Capturing dependencies in dependability studies is one of the most challenging tasks and requires suitable modeling techniques. In recent years the growing interest toward complex critical infrastructures and their interdependencies has solicited new efforts in the area of modeling and analysis of large interdependent systems. Cascading failures are a typical phenomenon of dependencies of components inside a system or among systems. New research in the area of the analysis of cascading phenomena has been also dictated by the recent occurrence of large scale electrical blackouts both in USA and in Europe that have caused the shortage of electrical power to millions of citizens. The present paper proposes to model cascading failures by means of Dynamic Bayesian Networks (DBN). In contrast with available techniques, DBN offer a good trade-off between the analytical tractability and the representation of the propagation of the cascading event. A failure scenario, taken from the literature, is considered as a final example.

Towards next generation infrastructures: an introduction to the contributions in this issue

Infrastructures are vital to our economy and society. The papers in this special issue address the state of the art in research on infrastructures design, management, and operation. A number of interrelated themes that allow analysing and structuring the vast number of research projects and themes have been identified. These themes have been taken from a large research programme 'Next Generation Infrastructures' and they comprise: infrastructures as complex adaptive systems, public values, flexible infrastructures, critical infrastructures and intelligent infrastructures. This paper briefly describes the themes and gives pointers to what papers can be found in this issue.

Hybrid Workflow and Bayesian Networks to Correlate Information in the Protection of Large Scale Critical Infrastructures

Safeguard is a system that aims to improve the dependability and survivability of large complex critical infrastructures by using distributed autonomous agents to monitor and protect them. This paper describes the embedding of a workflow management system within one of the Safeguard agents to support real-time correlation of information from anomaly detectors, intrusion detection systems and other system monitors. The workflow management system interprets workflow models, which are represented by augmented Petri Nets modelling generic forms of attack or failure. The workflow management system also triggers appropriate responses automatically according to the reasoning results of Bayesian networks linked to transitions in the workflows. A case study example from the management of electricity distribution networks will be presented.