This paper presents a systematic literature review on the application of digital twins in the energy sector. Initially, we generated an overview through a survey of prior reviews, independent of market vertical, then followed by a more detailed review concentrating on the power production and distribution domains, as per the NIST (National Institute of Standards and Technology) smart grid standard. We implemented a rigorous method, which included seven stages, beginning with the collection of 2238 articles. We observed that the energy sector range was too broad and filtered by generation and distribution during the practical screening, resulting in 275 for further screening. This amount was then condensed to 81 papers that matched the quality screening criteria for synthesis and examination. In summary, digital twin architectures and frameworks include five components: the physical entity, bidirectional communication, the virtual entity (with modeling and simulation), data management, and services. Our study contributed by determining that distribution management is the most pertinent application of digital twins in the distribution domain and fault diagnosis in the generation domain. Furthermore, we found that digital twins involve multiple stakeholders whose role is rarely discussed in studies, and we identified a similar absence of emphasis for security. Research on security often presents the digital twin as an additional layer of protection, yet rarely investigates the security of the digital twin by itself. The potential limitations of our study to answer some of the technical research questions may be because of the criteria for the selection of papers. However, as the emphasis of this study is on the energy sector, it enabled domain-specific findings for generation and distribution.

Autonomous transport is receiving increasing attention, with research and development activities already providing prototype implementations. In this article we focus on Autonomous Passenger Ships (APS) , which are being considered as a solution for passenger transport across urban waterways. The ambition of the authors has been to examine the safety and security implications of such a Cyber Physical System (CPS) , particularly focusing on threats that endanger the passengers and the operational environment of the APS. Accordingly, the article presents a new risk assessment approach based on a Failure Modes Effects and Criticality Analysis (FMECA) that is enriched with selected semantics and components of the MITRE ATT&CK framework, in order to utilize the encoded common knowledge and facilitate the expression of attacks. Then, the proposed approach is demonstrated through conducting a risk assessment for a communication architecture tailored to the requirements of APSs that were proposed in earlier work. Moreover, we propose a group of graph theory-based metrics for estimating the impact of the identified risks. The use of this method has resulted in the identification of risks and their corresponding countermeasures, in addition to identifying risks with limited existing mitigation mechanisms. The benefits of the proposed approach are the comprehensive, atomic, and descriptive nature of the identified threats, which reduce the need for expert judgment, and the granular impact estimation metrics that reduce the impact of bias. All these features are provided in a semi-automated approach to reduce the required effort and collectively are argued to enrich the design-level risk assessment processes with an updatable industry threat model standard, namely ATT&CK.

Safeguarding both safety and cybersecurity is paramount to the smooth and trustworthy operation of contemporary cyber physical systems, many of which support critical functions and services. As safety and security have been known to be interdependent, they need to be jointly considered in such systems. As a result, various approaches have been proposed to address safety and cybersecurity co-engineering in cyber physical systems. This paper provides a comprehensive survey of safety and cybersecurity co-engineering methods, and discusses relevant open issues and research challenges. Despite the extent of the existing literature, several aspects of the subject still remain to be fully addressed.

The technological leap of smart technologies and the Internet of Things has advanced the conventional model of the electrical power and energy systems into a new digital era, widely known as the Smart Grid. The advent of Smart Grids provides multiple benefits, such as self-monitoring, self-healing and pervasive control. However, it also raises crucial cybersecurity and privacy concerns that can lead to devastating consequences, including cascading effects with other critical infrastructures or even fatal accidents. This paper introduces a novel architecture, which will increase the Smart Grid resiliency, taking full advantage of the Software-Defined Networking (SDN) technology. The proposed architecture called SDN-microSENSE architecture consists of three main tiers: (a) Risk assessment, (b) intrusion detection and correlation and (c) self-healing. The first tier is responsible for evaluating dynamically the risk level of each Smart Grid asset. The second tier undertakes to detect and correlate security events and, finally, the last tier mitigates the potential threats, ensuring in parallel the normal operation of the Smart Grid. It is noteworthy that all tiers of the SDN-microSENSE architecture interact with the SDN controller either for detecting or mitigating intrusions.

Recent innovations in the smart city domain have led to the proposition of a new mode of transportation utilizing Autonomous Passenger Ships (APS) or ferries in inland waterways. The novelty of the APS concept influenced the cyber risk paradigm and led to different considerations regarding attack objectives, techniques as well as risk management approaches. The main factor that has led to this is the autoremote operational mode, which refers to autonomous operations and remote supervision and control in case of emergency. The autoremote operational mode influences the risk of cyber attacks due to the increased connectivity and reliance on technology for automating navigational functions. On the other hand, the presence of passengers without crew members imposes a safety risk factor in cyber attacks. In this paper, we propose a new cyber risk management approach for managing the cyber risks against cyber physical systems in general and Autonomous Passenger Ships in particular. Our proposed approach aims to improve the Defense-in-Depth risk management strategy with additional components from the Threat-Informed Defense strategy allowing for more evolved cyber risk management capabilities. Moreover, we have utilized the proposed cyber risk management approach for the proposition of a cybersecurity architecture for managing the cyber risks against an APS use case named milliAmpere2. Additionally, we present our results after conducting a Systematic Literature Review (SLR) in cybersecurity evaluation in the maritime domain. Then, the findings of the SLR were utilized for a suitable evaluation of the proposed risk management approach. Our findings suggest that our proposed risk management approach named Threat-Informed Defense-in-Depth is capable of enriching several risk management activities across different stages in the system development life cycle. Additionally, a comprehensive evaluation of the cybersecurity posture of milliAmpere2 has been conducted using several approaches including risk evaluation, simulation, checklist, and adversary emulation. Our evaluation has uncovered several limitations in the current cybersecurity posture and proposed actions for improvement.

There is a growing interest in using social robots in public spaces for indoor and outdoor applications. The threat landscape is an important research area being investigated and debated by various stakeholders. Objectives: This study aims to identify and synthesize empirical research on the complete threat landscape of social robots in public spaces. Specifically, this paper identifies the potential threat actors, their motives for attacks, vulnerabilities, attack vectors, potential impacts of attacks, possible attack scenarios, and mitigations to these threats. Methods: This systematic literature review follows the guidelines by Kitchenham and Charters. The search was conducted in five digital databases, and 1469 studies were retrieved. This study analyzed 21 studies that satisfied the selection criteria. Results: Main findings reveal four threat categories: cybersecurity, social, physical, and public space. Conclusion: This study completely grasped the complexity of the transdisciplinary problem of social robot security and privacy while accommodating the diversity of stakeholders’ perspectives. Findings give researchers and other stakeholders a comprehensive view by highlighting current developments and new research directions in this field. This study also proposed a taxonomy for threat actors and the threat landscape of social robots in public spaces.