Agent-based analysis and mitigation of failure for cyber-physical systems

Techniques exist for assessment, modeling, and simulation of physical and cyber infrastructures, respectively; but such isolated analysis is incapable of fully capturing the interdependencies that occur when they intertwine to create a cyber-physical system (CPS). The first contribution of this doctoral research includes qualitative representation of the operation of a CPS in a single multi-agent model. Dependable operation of a CPS is contingent upon correct interpretation of data describing the state of the system. To this end, we propose agent-based semantic interpretation services that extract useful information from raw sensor data. We utilize the summary schemas model to reconcile differences in data resolution, syntax, and semantics; and to facilitate imprecise query of databases that maintain historical information, including failure mitigation techniques. Another contribution of the research is in developing ontologies that enable automated reasoning in the classification and mitigation of failures in CPS operation. As a measure of dependability, we quantify the effectiveness of our proposed ontology-based approach in identifying correct mitigation techniques. Our methodology and models are applicable to a broad range of CPSs; however, they are described in the context of intelligent water distribution networks (WDNs), which are cyber-physical critical infrastructure systems responsible for reliable delivery of potable water. We illustrate the use of game theory in agent-based decision support for allocation of water. As a precursor to empirical validation with field data, we developed an integrated cyber-physical WDN simulator using EPANET and MATLAB, and illustrate the use of this simulator in validating our agent-based model and ontology-based approach to automated mitigation of failure --Abstract, page iii

Towards an Info-Symbiotic Decision Support System for Disaster Risk Management

This paper outlines a framework for an info-symbiotic modelling system using cyber-physical sensors to assist in decision-making. Using a dynamic data-driven simulation approach, this system can help with the identification of target areas and resource allocation in emergency situations. Using different natural disasters as exemplars, we will show how cyber-physical sensors can enhance ground level intelligence and aid in the creation of dynamic models to capture the state of human casualties. Using a virtual command & control centre communicating with sensors in the field, up-to-date information of the ground realities can be incorporated in a dynamic feedback loop. Using other information (e.g. Weather models) a complex and rich model can be created. The framework adaptively manages the heterogeneous collection of data resources and uses agent-based models to create what-if scenarios in order to determine the best course of action

A Declarative Goal-oriented Framework for Smart Environments with LPaaS

Smart environments powered by the Internet of Things aim at improving our daily lives by automatically tuning ambient parameters (e.g. temperature, interior light) and by achieving energy savings through self-managing cyber-physical systems. Commercial solutions, however, only permit setting simple target goals on those parameters and do not consider mediating conflicting goals among different users and/or system administrators, and feature limited compatibility across different IoT verticals. In this article, we propose a declarative framework to represent smart environments, user-set goals and customisable mediation policies to reconcile contrasting goals encompassing multiple IoT systems. An open-source Prolog prototype of the framework is showcased over two lifelike motivating examples

A Semantic Agent Framework for Cyber-Physical Systems

The development of accurate models for cyber-physical systems (CPSs) is hampered by the complexity of these systems, fundamental differences in the operation of cyber and physical components, and significant interdependencies among these components. Agent-based modeling shows promise in overcoming these challenges, due to the flexibility of software agents as autonomous and intelligent decision-making components. Semantic agent systems are even more capable, as the structure they provide facilitates the extraction of meaningful content from the data provided to the software agents. In this book chapter, we present a multi-agent model for a CPS, where the semantic capabilities are underpinned by sensor networks that provide information about the physical operation to the cyber infrastructure. As a specific example of the semantic interpretation of raw sensor data streams, we present a failure detection ontology for an intelligent water distribution network as a model CPS. The ontology represents physical entities in the CPS, as well as the information extraction, analysis and processing that takes place in relation to these entities. The chapter concludes with introduction of a semantic agent framework for CPS, and presentation of a sample implementation of the framework using C++

Measures of reconfigurability and its key characteristics in intelligent manufacturing systems

\In recent years, the fields of reconfigurable manufacturing systems, holonic manufacturing systems, and multi-agent systems have made technological advances to support the ready reconfiguration of automated manufacturing systems. While these technological advances have demonstrated robust operation and been qualitatively successful in achieving reconfigurability, limited effort has been devoted to the measurement of reconfigurability in the resultant systems. Hence, it is not clear (1) to which degree these designs have achieved their intended level of reconfigurability, (2) which systems are indeed quantitatively more reconfigurable and (3) how these designs may overcome their design limitations to achieve greater reconfigurability in subsequent design iterations. Recently, a reconfigurability measurement process based upon axiomatic design knowledge base and the design structure matrix has been developed. Together, they provide quantitative measures of reconfiguration potential and ease. This paper now builds upon these works to provide a set of composite reconfigurability measures. Among these are measures for the key characteristics of reconfigurability: integrability, convertibility, and customization, which have driven the qualitative and intuitive design of these technological advances. These measures are then demonstrated on an illustrative example followed by a discussion of how they adhere to requirements for reconfigurability measurement in automated and intelligent manufacturing systems

Proceedings of the 4th Workshop of the MPM4CPS COST Action

Proceedings of the 4th Workshop of the MPM4CPS COST Action with the presentations delivered during the workshop and papers with extended versions of some of them

IT affordances and reconciling alternative modes of evidence giving in cyberinfrastructure: the case of Climate Change Research

This qualitative study was conducted to examine how multi-disciplinary environmental science teams utilize cyber-infrastructure to generate and assess evidence as part of their boundary spanning research. We find that this interdisciplinary research is difficult due to the divergent institutional logics of the team members (represented by the tenets of their communities of practices, dominant epistemological frameworks and dispositions towards data) which force researchers to synthesize incommensurate forms of data and warrants into their scientific arguments. We examine how the affordances enacted in the cyber-infrastructure enabled one environmental science team to ameliorate these challenges. This study contributes to the nascent literature on the new forms of evidence giving within scientific fields by building a theoretical framework to account for how affordances enacted within cyber-infrastructure can assist researchers as they negotiate the conflicting institutional logics associated with diverse fields. We conclude by discussing how these issues impact the effectiveness of interdisciplinary inquir

Requirements-driven mediation for collaborative security

Security is concerned with the protection of assets from intentional harm. Secure systems provide capabilities that enable such protection to satisfy some security requirements. In a world increasingly populated with mobile and ubiquitous computing technology, the scope and boundary of security systems can be uncertain and can change. A single functional component, or even multiple components individually, are often insufficient to satisfy complex security requirements on their own. Adaptive security aims to enable systems to vary their protection in the face of changes in their operational environment. Collaborative security, which we propose in this paper, aims to exploit the selection and deployment of multiple, potentially heterogeneous, software-intensive components to collaborate in order to meet security requirements in the face of changes in the environment, changes in assets under protection and their values, and the discovery of new threats and vulnerabilities. However, the components that need to collaborate may not have been designed and implemented to interact with one another collaboratively. To address this, we propose a novel framework for collaborative security that combines adaptive security, collaborative adaptation and an explicit representation of the capabilities of the software components that may be needed in order to achieve collaborative security. We elaborate on each of these framework elements, focusing in particular on the challenges and opportunities afforded by (1) the ability to capture, represent, and reason about the capabilities of different software components and their operational context, and (2) the ability of components to be selected and mediated at runtime in order to satisfy the security requirements. We illustrate our vision through a collaborative robotic implementation, and suggest some areas for future work

Security as a context, generative force, and policy concern for the co-production of cyberspace: historical overview since WWII until the end of the Cold War

Many cybersecurity literature take the 1990s as a starting point to trace the process of securitising cyberspace; implicitly suggesting that it initially emerged as a non-security sector, which was then securitised. Although it is true that ‘cyberspace’ and ‘cybersecurity’ were novel terms at that period, their ontological status cannot be reduced to their mere utterances. If the security of cyberspace as a constructed metaphor signifies the security of computers and networks, with all their associated software, hardware, and data - technologies that have long historical roots - then an ahistorical approach to studying its evolution would be both insufficient and over-simplified. Therefore, this paper aims to prove that security has always been an integral part of the co-production of cyberspace: As a context in which it was developed, as a generative force behind many of its technologies, and as a policy concern in different phases of its evolution, since the emergence of the first computer till the advent of the internet. It seeks to prove that the history of cyberspace is better analysed as a complex process of restructuring, not just technically, but also politically and socially, in which the interests of various actors competed, and security considerations were intertwined with technical ones, and in many respects coproduced them. This analysis is important to show that security was not imposed on cyberspace by political discourses, but has always been intrinsic to the existence of its components and technologies. Besides, it challenges the deterministic accounts of the development of computers and networks, which present them in an idealistic, utopian image as being solely products of civilian and academic efforts