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

Risk Assessment of a Wind Turbine: A New FMECA-Based Tool With RPN Threshold Estimation

A wind turbine is a complex system used to convert the kinetic energy of the wind into electrical energy. During the turbine design phase, a risk assessment is mandatory to reduce the machine downtime and the Operation & Maintenance cost and to ensure service continuity. This paper proposes a procedure based on Failure Modes, Effects, and Criticality Analysis to take into account every possible criticality that could lead to a turbine shutdown. Currently, a standard procedure to be applied for evaluation of the risk priority number threshold is still not available. Trying to fill this need, this paper proposes a new approach for the Risk Priority Number (RPN) prioritization based on a statistical analysis and compares the proposed method with the only three quantitative prioritization techniques found in literature. The proposed procedure was applied to the electrical and electronic components included in a Spanish 2 MW on-shore wind turbine

A Systematic Approach To Portfolio Creation In Restructured Electricity Markets

This paper determines and compares the efficacy of systematic approaches to portfolio construction using hourly assets from the PJM (Pennsylvania-New Jersey-Maryland) Independent System Operator (PJMISO). The two models addressed herein are an unconditional mean-covariance model using ordinary least squares (OLS) estimation and a lagged seemingly unrelated regression (SUR) model using feasible generalized least squares (FGLS) estimation. Despite the abundance of quantitative research on electricity markets, market participants are known for doing anecdotal analysis on the qualitative features of the market, e.g. weather patterns, transmission and generation outages, gas prices, etc. to construct daily portfolios and manage risk. Further, there is a lack of academic research that takes a practical approach to daily, portfolio risk in these markets. This paper bridges the gap between academic and industry analysis by incorporating quantitative analysis into a practical, systematic approach to portfolio construction. To test for and compare the efficacy of optimized daily portfolios, this paper will simulate portfolios using realized returns from the PJMISO market

An advanced risk analysis approach for container port safety evaluation

Risk analysis in seaports plays an increasingly important role in ensuring port operation reliability, maritime transportation safety and supply chain distribution resilience. However, the task is not straightforward given the challenges, including that port safety is affected by multiple factors related to design, installation, operation and maintenance and that traditional risk assessment methods such as quantitative risk analysis cannot sufficiently address uncertainty in failure data. This paper develops an advanced Failure Mode and Effects Analysis (FMEA) approach through incorporating Fuzzy Rule-Based Bayesian Networks (FRBN) to evaluate the criticality of the hazardous events (HEs) in a container terminal. The rational use of the Degrees of Belief (DoB) in a fuzzy rule base (FRB) facilitates the implementation of the new method in Container Terminal Risk Evaluation (CTRE) in practice. Compared to conventional FMEA methods, the new approach integrates FRB and BN in a complementary manner, in which the former provides a realistic and flexible way to describe input failure information while the latter allows easy updating of risk estimation results and facilitates real-time safety evaluation and dynamic risk-based decision support in container terminals. The proposed approach can also be tailored for wider application in other engineering and management systems, especially when instant risk ranking is required by the stakeholders to measure, predict and improve their system safety and reliability performance

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

AbstractThe 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.</jats:p

Quantitative Proteomic (iTRAQ) Analysis of 1st Trimester Maternal Plasma Samples in Pregnancies at Risk for Preeclampsia

A current major obstacle is that no reliable screening markers exist to detect pregnancies at risk for preeclampsia. Quantitative proteomic analysis employing isobaric labelling (iTRAQ) has been suggested to be suitable for the detection of potential plasma biomarkers, a feature we recently verified in analysis of pregnancies with Down syndrome foetuses. We have now examined whether this approach could yield biomarkers to screen pregnancies at risk for preeclampsia. In our study, we used maternal plasma samples obtained at 12 weeks of gestation, six from women who subsequently developed preeclampsia and six with uncomplicated deliveries. In our analysis, we observed elevations in 10 proteins out of 64 proteins in the preeclampsia study group when compared to the healthy control group. These proteins included clusterin, fibrinogen, fibronectin, and angiotensinogen, increased levels of which are known to be associated with preeclampsia. An elevation in the immune-modulatory molecule, galectin 3 binding protein, was also noted. Our pilot study, therefore, indicates that quantitative proteomic iTRAQ analysis could be a useful tool for the detection of new preeclampsia screening markers

Relative seismic and tsunami risk assessment for Stromboli Island (Italy)

An innovative method of estimating the relative risk of buildings exposed to seismic and tsunami hazards in volcanic islands is applied to Stromboli (Italy), a well-known stratovolcano affected by moderate earthquakes and mass-flow-induced tsunamis. The method uses a pre-existing quali-quantitative analysis to assess the relative risk indices of buildings, which provide comparative results useful for prioritisation purposes, in combination with a historical-geographical settlement analysis consistent with the ‘territorialist’ approach to the urban and regional planning and design. The quali-quantitative analysis is based on a new proposed survey-sheet model, useful to collect building information necessary for the relative risk estimation, whereas the historical-geographical investigation is based on the multi-temporal comparison of aerial and satellite images. The proposal to combine two consolidated methods represents an innovation in estimating relative risk. Considering that Stromboli Island had never been subjected to similar analyses, the results of the relative seismic risk assessment are novel and moreover identify buildings with a fairly-low and spatially-uniform relative risk. The results of the relative tsunami risk assessment are consistent with results of similar past studies, identifying buildings with a higher relative risk index on the northern coast of the island. The combined use of a building-by-building survey with a multi-temporal analysis of settlements allows obtaining a higher detail than previously available for the region. If adequately modified, the proposed combination of methods allows assessing relative risk also considering other geo-environmental hazards and their cascading effects, in a multi-hazard risk assessment perspective

On the treatment of uncertainty in innovation projects

Innovations encounter a relatively high level of uncertainty in their lifecycle path. As innovations are about implementing a new idea, they suffer from a shortage or lack of knowledge dependent on and directly proportional to the radical quality of novelty. They lack information to predict the future and face (high) uncertainty in the background knowledge used for the risk assessment. Incomplete information causes innovation risk analysts to assign subjective assumptions to simplify system models developed for innovation risk assessment. Subjective and non-subjective assumptions as uncertain assumptions are part of the background knowledge and source of uncertainty. This thesis tries to assess and treat innovation assumptions uncertainties by proposing a hybrid model which comprises the semi-quantitative risk assessment (SQRA) approach, extended semi-quantitative risk assessment (EQRA) approach, and knowledge dimension method. SQRA and EQRA highlight the criticality of assumptions and present a systematic approach to assess and treat assumption uncertainties. SQRA applies probabilistic analysis to conduct an assumptions risk assessment, and EQRA provides innovation managers with guidance on developing strategies to follow up uncertain assumptions over the process implementation. The knowledge dimension technique evaluates and communicates the strength of background knowledge applied in assumptions risk assessment to innovation decision-makers expressing whole uncertainty aspects in the background knowledge (assumptions, data, models, and expert judgment). The model can effectively contribute to innovation risks and uncertainties management during the project execution.2021-09-29T16:30:09

Developing a Tailored RBS Linking to BIM for Risk Management of Bridge Projects

Purpose – The purpose of this paper is to address the current theoretical gap in integrating knowledge and experience into Building Information Model (BIM) for risk management of bridge projects by developing a tailored Risk Breakdown Structure (RBS) and formalising an active link between the resulting RBS and BIM. Design/methodology/approach – A three-step approach is used in this study to develop a tailored RBS for bridge projects and a conceptual model for the linkage between the RBS and BIM. First, the integrated bridge information model is in concept separated into four levels of contents (LOCs) and six technical systems based on analysis of the Industry Foundation Classes specification, a critical review of previous studies and authors’ project experience. The second step develops a knowledge-based risk database through an extensive collection of risk data, a process of data mining, and further assessment and translation of data. A critical analysis is conducted in the last step to determine on which level the different risks should be allocated to bridge projects and to propose a conceptual model for linking the tailored RBS to the four LOCs and six technical systems of BIM. Findings – The findings suggest that the traditional method and BIM can be merged as an integrated solution for risk management by establishing the linkage between RBS and BIM. This solution can take advantage of both the traditional method and BIM for managing risks. On the one hand, RBS enables risk information to be stored in a formal structure, used and communicated effectively. On the other hand, some features of BIM such as 3D visualisation and 4D construction scheduling can facilitate the risk identification, analysis, and communication at an early project stage. Research limitations/implications – A limitation is that RBS is a qualitative technique and only plays a limited role in quantitative risk analysis. As a result, when implementing this proposed method, further techniques may be needed for assisting quantitative risk analysis, evaluation, and treatment. Another limitation is that the proposed method has not yet been implemented for validation in practice. Hence, recommendations for future research are to: improve the quantitative risk analysis and treatment capabilities of this proposed solution; develop computer tools to support the solution; integrate the linkage into a traditional workflow; and test this solution in some small and large projects for validation. Practical implications – Through linking risk information to BIM, project participants could check and review the linked information for identifying potential risks and seeking possible mitigation measures, when project information is being transferred between different people or forwarded to the next phase. Originality/value – This study contributes to the theoretical development for aligning traditional methods and BIM for risk management, by introducing a new conceptual model for linking RBS to BIM