Digital Twins and the Future of their Use Enabling Shift Left and Shift Right Cybersecurity Operations

Digital Twins (DTs), optimize operations and monitor performance in Smart Critical Systems (SCS) domains like smart grids and manufacturing. DT-based cybersecurity solutions are in their infancy, lacking a unified strategy to overcome challenges spanning next three to five decades. These challenges include reliable data accessibility from Cyber-Physical Systems (CPS), operating in unpredictable environments. Reliable data sources are pivotal for intelligent cybersecurity operations aided with underlying modeling capabilities across the SCS lifecycle, necessitating a DT. To address these challenges, we propose Security Digital Twins (SDTs) collecting realtime data from CPS, requiring the Shift Left and Shift Right (SLSR) design paradigm for SDT to implement both design time and runtime cybersecurity operations. Incorporating virtual CPS components (VC) in Cloud/Edge, data fusion to SDT models is enabled with high reliability, providing threat insights and enhancing cyber resilience. VC-enabled SDT ensures accurate data feeds for security monitoring for both design and runtime. This design paradigm shift propagates innovative SDT modeling and analytics for securing future critical systems. This vision paper outlines intelligent SDT design through innovative techniques, exploring hybrid intelligence with data-driven and rule-based semantic SDT models. Various operational use cases are discussed for securing smart critical systems through underlying modeling and analytics capabilities.Comment: IEEE Submitted Paper: Trust, Privacy and Security in Intelligent Systems, and Application

Teaching co-simulation basics through practice

International audienceCyber-physical system representation is one of the current challenges in Modeling and Simulation. In fact, multi-domain modeling requires new approaches to rigorously deal with it. Co-simulation, one of the approaches, lets modelers use several M&S tools in collaboration. The challenge is to find a way to enable co-simulation use for non-IT experts while being aware of assumptions and limitations involved. This paper deals with co-simulation basic principles teaching through practice. we propose an iterative and modular co-simulation process supported by a DSL-based environment for the MECSYCO co-simulation platform. Through a thermal use case, we are able to introduce co-simulation in a 4 hours tutorial destined to our students. Efficient energy management is one of this century challenges. The current trend to deal with it is to build cyber-physical system (CPS) [Kleissl and Agarwal, 2010]. CPS are physical systems monitored and supervised by one or several computers through a communication networks [Ra-jkumar et al., 2010]. Smart-grids are examples of CPS where the energy network is coupled with a communication network to enable remote monitoring and control. The Modeling and Simulation (M&S) of such systems is one of the current challenges in M&S due to the inter-disciplinary issues they raise. It requests the development of new methods which deal with multi-domain by integrating each expert point of view in the same rigorous and efficient M&S activity. Co-simulation [Gomes et al., 2018] is a way to achieve it

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++

Trustworthiness in Mobile Cyber Physical Systems

Computing and communication capabilities are increasingly embedded in diverse objects and structures in the physical environment. They will link the ‘cyberworld’ of computing and communications with the physical world. These applications are called cyber physical systems (CPS). Obviously, the increased involvement of real-world entities leads to a greater demand for trustworthy systems. Hence, we use "system trustworthiness" here, which can guarantee continuous service in the presence of internal errors or external attacks. Mobile CPS (MCPS) is a prominent subcategory of CPS in which the physical component has no permanent location. Mobile Internet devices already provide ubiquitous platforms for building novel MCPS applications. The objective of this Special Issue is to contribute to research in modern/future trustworthy MCPS, including design, modeling, simulation, dependability, and so on. It is imperative to address the issues which are critical to their mobility, report significant advances in the underlying science, and discuss the challenges of development and implementation in various applications of MCPS

Secure and dependable cyber-physical system architectures

The increased computational power and connectivity in modern Cyber-Physical Systems (CPS) inevitably introduce more security vulnerabilities. The concern about CPS security is growing especially because a successful attack on safety-critical CPS (e.g., avionics, automobile, smart grid, etc.) can result in the safety of such systems being compromised, leading to disastrous effects, from loss of human life to damages to the environment as well as critical infrastructure. CPS poses unique security challenges due to its stringent design and implementation requirements. This dissertation explores the structural differences of CPS compared to the general-purpose systems and utilizes the intrinsic characteristics of CPS as an asymmetric advantage to thwart and detect security attacks to safety-critical CPS. The dissertation presents analytic techniques and system design principles to enhance the security and dependability of CPS, with particular focus on (a) modeling and reasoning about the logical and physical behaviors of CPS and (b) architectural and operating-system supports for trusted, efficient run-time monitoring as well as attack-resiliency