Cen Nan

''System-of-systems'' approach for interdependent critical infrastructures

The study of the interdependencies within critical infrastructures (CI) is a growing field of research as the importance of potential failure propagation among infrastructures may lead to cascades affecting all supply networks. New powerful methods are required to model and describe such ‘‘systems-ofsystems’’ (SoS) as a whole. An overall model is required to provide security and reliability assessment taking into account various kinds of threats and failures. A significant challenge associated with this model may be to create ‘‘what-if’’ scenarios for the analysis of interdependencies. In this paper the interdependencies between industrial control systems (ICS), in particular SCADA (Supervisory Control and Data Acquisition), and the underlying critical infrastructures to address the vulnerabilities related to the coupling of these systems are analyzed. The modeling alternatives for system-of-systems, integrated versus coupled models, are discussed. An integrated model contains detailed low level models of (sub)systems as well as a high level model, covering all hierarchical levels. On the other hand, a coupled model aggregates different simulated outputs of the low level models as inputs at a higher level. Strengths and weaknesses of both approaches are analyzed and a model architecture for SCADA and the ‘‘system under control’’ are proposed. Furthermore, the HLA simulation standard is introduced and discussed in this paper as a promising approach to represent interdependencies between infrastructures. To demonstrate the capabilities of the HLA standard for the interdependencies study, an exemplary application and some first results are also briefly presented in this paper.

Adopting HLA standard for interdependency study

In recent decades, modern Critical Infrastructure (CI) has become increasingly automated and interlinked as more and more resources and information are required to maintain its day-to-day operation. A system failure, or even just a service debilitation, of any CI may have significant adverse effects on other infrastructures it is connected/interconnected with. It is vital to study the interdependencies within and between CIs and provide advanced modeling and simulation techniques in order to prevent or at least minimize these adverse effects. The key limitation of traditional mathematical models such as complex network theory is their lacking the capabilities of providing sufficient insights into interrelationships between CIs due to the complexities of these systems. A comprehensive method, a hybrid approach combining various modeling/simulation techniques in a distributed simulation environment, is presented in this paper. High Level Architecture (HLA) is an open standard (IEEE standard 1516) supporting simulations composed of different simulation components, which can be regarded as the framework for implementing such a hybrid approach. The concept of adopting HLA standard for the interdependency study is still under discussion by many researchers. Whether or not this HLA standard, or even the distributed simulation environment, is able to meet desired model/simulation requirements needs to be carefully examined. This paper presents the results from our experimental test-bed, which recreates the architecture of a typical Electricity Power Supply System (EPSS) with its own Supervisory Control and Data Acquisition (SCADA) system, for the purpose of investigating the capabilities of the HLA technique as a standard to perform interdependency studies.

A quantitative method for assessing resilience of interdependent infrastructures

The importance of understanding system resilience and identifying ways to enhance it, especially for interdependent infrastructures our daily life depends on, has been recognized not only by academics, but also by the corporate and public sectors. During recent years, several methods and frameworks have been proposed and developed to explore applicable techniques to assess and analyze system resilience in a comprehensive way. However, they are often tailored to specific disruptive hazards/events, or fail to properly include all the phases such as absorption, adaptation, and recovery. In this paper, a quantitative method for the assessment of the system resilience is proposed. The method consists of two components: an integrated metric for system resilience quantification and a hybrid modeling approach for representing the failure behavior of infrastructure systems. The feasibility and applicability of the proposed method are tested using an electric power supply system as the exemplary infrastructure. Simulation results highlight that the method proves effective in designing, engineering and improving the resilience of infrastructures. Finally, system resilience is proposed as a proxy to quantify the coupling strength between interdependent infrastructures.

Analyzing vulnerabilities between SCADA system and SUC due to interdependencies

Interdependencies within and among Critical Infrastructures (CIs), e.g., between Industrial Control Systems (ICSs), in particular Supervisory Control and Data Acquisition (SCADA) system, and the underlying System Under Control (SUC), have dramatically increased the overall complexity of related systems, causing the emergence of unpredictable behaviors and making them more vulnerable to cascading failures. It is vital to get a clear understanding of these often hidden interdependency issues and tackle them with advanced modeling and simulation techniques. In this paper, vulnerabilities due to interdependencies between these two exemplary systems (SCADA and SUC) are investigated and analyzed comprehensively using a modified five-step methodical framework. Furthermore, suggestions for system performance improvements based on the investigation and analysis results, which could be useful to minimize the negative effects and improve their coping capacities, are also presented in this paper.

Creating a simulation environment for critical infrastructure interdependencies study

The critical infrastructures (CIs) on which our daily life depends are mutually interdependent. What happens to one infrastructure can directly or indirectly affect another infrastructure or maybe even more. The development of advanced techniques of modeling and simulation is significant for the interdependencies study between CIs. In this paper, an approach to model critical infrastructures as well as adopting HLA (High Level Architecture) standard to simulate the interoperations between individual models under system-of-systems design architecture is proposed. Two examples of interdependent systems (CIs), which are studied in this approach, are : Electric Power Supply (EPS) System and Supervisory Control and Data Acquisition (SCADA) System.

Exploring impacts of single failure propagation between SCADA and SUC

Critical infrastructures (CI) deserve increased attention as our societies simply rely on most of their goods and services they are expected to continuously supply. The study of the interdependencies within and among CI is an emerging research field since modern CI are becoming increasingly vital as well as automated and interlinked in complex ways to maintain their daily operations. A failure within any CI or even loss of its continuous service may be damaging enough to society and economy while cascading failures across boundaries have the potential for multi-infrastructural collapse with unprecedented negative consequences. In this paper, the interdependencies between Industrial Control Systems (ICS), in particular SCADA (Supervisory Control and Data Acquisition), and the underlying System Under Control (SUC) are explored and studied using advanced model/simulation techniques. A single failure propagation experiment that analyzes a typical substation of the Electricity Power Supply System (EPSS), comprising components from both SUC and SCADA is developed to visualize the propagation of cascading events across boundaries and evaluate negative impacts on the service availability of the system due to interdependencies related problems.

Building an Integrated Metric for Quantifying the Resilience of Interdependent Infrastructure Systems

Resilience is a dynamic multi-faceted term and complements other terms commonly used in risk analysis, e.g., reliability, availability, vulnerability, etc. The importance of fully understanding system resilience and identifying ways to enhance it, especially for infrastructure systems our daily life depends on, has been recognized not only by researchers, but also by public. During last decade, researchers have proposed different methods and frameworks to quantify/assess system resilience. However, they are tailored to specific disruptive hazards/events, or fail to properly include all the phases such as mitigation, adaptation and recovery. In this paper, an integrated metric for resilience quantification with capabilities of incorporating different performance measures is proposed, which can be used to quantify the performance of interdependent infrastructure systems in a more comprehensive way. The feasibility and applicability of the proposed metric will be tested using an electric power supply system as the exemplary system with the help of advanced modelling and simulation techniques. Furthermore, the discussion related to the effects of interdependencies among systems on their resilience capabilities is also included in this paper.

Multilayer hybrid modeling framework for the performance assessment of interdependent critical infrastructures

Abstract The heterogeneity and tight coupling of modern critical infrastructures make it challenging to create tractable descriptions of their emergent behaviors. Classic analytical methods do not provide adequate insights into system behavior and do not fully capture the complexity of infrastructure interdependencies. Meanwhile, modeling approaches developed to represent the diverse physics and operations of critical infrastructures fail to provide a unifying framework for analyzing performance. This paper attempts to address these challenges by proposing a multilayer hybrid modeling framework that supports the detailed understanding and holistic analysis of critical infrastructure systems. A critical infrastructure is viewed as a combination of integrated subsystems structured in interdependent layers: (i) systems under control; (ii) operational control system; and (iii) human-organizational social system. The systems under control and operational control system constitute the technical components of a critical infrastructure. The human-organizational social system is the non-technical component of a critical infrastructure that captures the human and social factors that influence system performance. The modeling framework is demonstrated using the Swiss electric power supply system, which comprises three interdependent layers: the power grid, a supervisory control and data acquisition (SCADA) system and human operators. The framework can help guide the identification of strategies for designing, maintaining and enhancing the performance of critical infrastructures.

Hidden Vulnerabilities Due to Interdependencies between Two Systems

Critical infrastructures (CIs) deserve increased attention as our societies simply rely on most of the goods and services they are expected to continuously supply. Interdependencies within and among CIs have dramatically increased the overall complexity of related infrastructure systems, making them more vulnerable to cascading failures with widespread unpredicted consequences. It is vital to get a clear understanding of these often hidden interdependency issues and tackle them through advanced techniques. In this paper, the interdependencies between Industrial Control Systems (ICS), in particular the SCADA (Supervisory Control and Data Acquisition) system, and the underlying System Under Control (SUC) are identified and assessed using modeling/simulation methods by following a modified 4-step methodical framework. This paper mainly focuses on those techniques and analytical experiments developed for the essential step of this methodical framework, the in-depth analysis, i.e., applying a hybrid modeling/simulation approach and three in-depth experiments.

Abnormal Process Condition Prediction (Fault Diagnosis) Using G2 Expert System

Abnormal operating conditions (faults) in industrial processes have the potential to cause loss of production, loss of life and/or damage to environment. The accidents, which could cost industry billons of dollars per year, can be prevented if abnormal process condition is predicted and controlled in advance. Due to the increased process complexity and instability in operating conditions, the existing control system may have a limited ability to provide practical assistance to both operators and engineers. Advanced software applications, based on expert system, has the potential to assist engineers in monitoring, detecting, diagnosing abnormal condition and thus providing safe guards against unexpected process conditions.