Dynamic real-time risk analytics of uncontrollable states in complex internet of things systems, cyber risk at the edge

The Internet of Things (IoT) triggers new types of cyber risks. Therefore, the integration of new IoT devices and services requires a self-assessment of IoT cyber security posture. By security posture this article refers to the cybersecurity strength of an organisation to predict, prevent and respond to cyberthreats. At present, there is a gap in the state of the art, because there are no self-assessment methods for quantifying IoT cyber risk posture. To address this gap, an empirical analysis is performed of 12 cyber risk assessment approaches. The results and the main findings from the analysis is presented as the current and a target risk state for IoT systems, followed by conclusions and recommendations on a transformation roadmap, describing how IoT systems can achieve the target state with a new goal-oriented dependency model. By target state, we refer to the cyber security target that matches the generic security requirements of an organisation. The research paper studies and adapts four alternatives for IoT risk assessment and identifies the goal-oriented dependency modelling as a dominant approach among the risk assessment models studied. The new goal-oriented dependency model in this article enables the assessment of uncontrollable risk states in complex IoT systems and can be used for a quantitative self-assessment of IoT cyber risk posture

Quantifying Economic Benefits for Rail Infrastructure Projects

This project identifies metrics for measuring the benefit of rail infrastructure projects for key stakeholders. It is important that stakeholders with an interest in community economic development play an active role in the development of the rail network. Economic development activities in both rural and urban settings are essential if a nation is to realize growth and prosperity. Many communities have developed goals and visions to establish an economic development program, but they often fail to achieve their goals due to uncertainties during the project selection and planning process. Communities often select a project from a vast pool of ideas with only limited capital available for investment. Selecting the right project at the right time becomes imperative for economic and community development. This process is significantly hampered by limited methods for quantifying the economic benefit to key stakeholders. Four methodologies are used in this project to determine the most useful tools for quantifying benefit given the availability of data, relevant expertise, and other information

Disaster management in smart cities

The smart city concept, in which data from different systems are available, contains a multitude of critical infrastructures. This data availability opens new research opportunities in the study of the interdependency between those critical infrastructures and cascading effects solutions and focuses on the smart city as a network of critical infrastructures. This paper proposes an integrated resilience system linking interconnected critical infrastructures in a smart city to improve disaster resilience. A data-driven approach is considered, using artificial intelligence and methods to minimize cascading effects and the destruction of failing critical infrastructures and their components (at a city level). The proposed approach allows rapid recovery of infrastructures’ service performance levels after disasters while keeping the coverage of the assessment of risks, prevention, detection, response, and mitigation of consequences. The proposed approach has the originality and the practical implication of providing a decision support system that handles the infrastructures that will support the city disaster management system—make the city prepare, adapt, absorb, respond, and recover from disasters by taking advantage of the interconnections between its various critical infrastructures to increase the overall resilience capacity. The city of Lisbon (Portugal) is used as a case to show the practical application of the approach.info:eu-repo/semantics/publishedVersio

Efficient systems for the securities transaction industry : a framework for the European Union

This paper provides a framework for the securities transaction industry in the EU to understand the functions performed, the institutions involved and the parameters concerned that shape market and ownership structure. Of particular interest are microeconomic incentives of the industry players that can be in contradiction to social welfare. We evaluate the three functions and the strategic parameters - the boundary decision, the communication standard employed and the governance implemented - along the lines of three efficiency concepts. By structuring the main factors that influence these concepts and by describing the underlying trade-offs among them, we provide insight into a highly complex industry. Applying our framework, the paper describes and analyzes three consistent systems for the securities transaction industry. We point out that one of the systems, denoted as 'contestable monopolies', demonstrates a superior overall efficiency while it might be the most sensitive in terms of configuration accuracy and thus difficult to achieve and sustain