Beyond the environmental drawback of fossil energy sources, energy security remains a salient concern for economic development and environmental sustainability. This explains why the influence of ...energy security and its components (economic, geopolitical, reliability, environmental) on the price of crude oil commodity, especially in the United States of America, is considered in this study up to the period 2040 (i.e., from 1970 to 2040). Using the Kernel-Based Regularized Least Squares (KRLS) approach supported by the robustness of the quantile regression, the result shows an increase in aggregate energy security risk spur crude oil price by an elasticity of ∼0.9. With a positive impact on oil price, the economic, geopolitical, and reliability perspectives of energy security risk exhibit respective elasticity of ∼2.0, ∼0.6, and ∼0.7, thus confirming that a positive shock in each aspect aggravates the oil price hike in the country. Contrarily, an increase in environmental risk could spiral a decline and an inelastic (∼−1.5) change in crude oil price, thus suggesting a desirable net zero future and a significant crash in oil price arising from clean and alternative energy source adoption. Furthermore, retail electricity price and energy expenditures are used as control variables, and crude oil prices respond positively and negatively to the increase in energy expenditures and electricity price, respectively. Several accounts of policy insights are highlighted in these results.
•Energy security positively drives crude oil price in USA up to 2040.•Energy security via economic, geopolitics, and reliability positively drives oil price.•Energy security via environmental risk causes oil price to decline.•Retail electricity prices cause crude oil price to plummet.•Crude oil price responds positively to increase in energy expenditures.
Analysis of healthcare big data Lv, Zhihan; Qiao, Liang
Future generation computer systems,
August 2020, 2020-08-00, Letnik:
109
Journal Article
Recenzirano
In order to explore the development of healthcare in China and the privacy and security risk factors in medical data under the background of big data, the development status of China’s healthcare ...sector is analyzed. The questionnaire is used to analyze the privacy and security risk factors of healthcare big data and protection measures are put forward based on the data privacy and security risk factors in the context of cloud services in the literature. The results show that in recent years, the number of health institutions, the number of medical personnel, the assets of medical institutions, the per capita hospitalization cost, and the insured population all show a trend of increasing year by year; while in 2017, the crude mortality rate of malignant tumor patients was the highest in China, and the mortality rate of rural patients was higher than that of urban patients. The results of the questionnaire show that the probability of data analysis, medical treatment process, disease diagnosis process, lack of protective measures, and imperfect access system is all greater than 0.8 when medical care big data is oriented to cloud services. Based on this, two levels of privacy protection measures are proposed: technology and management. It indicates that medical institutions need to pay attention to data privacy protection and grasp the use of digital medical data to provide decision support for subsequent medical data analysis.
•The development status of China’s healthcare sector is analyzed.•The results of the questionnaire show that the probability of data analysis, medical treatment process, disease diagnosis process, lack of protective measures, and imperfect access system is all greater than 0.8 when medical care big data is oriented to cloud services.•It indicates that medical institutions need to pay attention to data privacy protection and grasp the use of digital medical data to provide decision support for subsequent medical data analysis.
Security incidents around the world causes enormous loss in terms of life, economy, and environment. The 9/11 ′triggered the serious onset of research initiatives in the field of security with a more ...specific focus on the protection of high sensitive and hazardous facilities. It is well known that technology is advancing in a very rapid phase, proportionally increasing the security risk of the facilities. Conventional deterministic risk techniques widely found their applications in the earlier stage but owing to the increasing dynamic nature of the security risk, probabilistic dynamic risk assessment models were developed over time. In this article, the authors attempted to present the evolution of security risk concepts, their present status, and their future scope in a precise and consolidated form. The last 20 years of development in the security risk assessment concept involving deterministic and dynamic risk assessment models and applications in security risk assessment relevant to physical security are discussed in this article. The objective of the article is to outline the past, current and future directions of security risk highlighting their strength, weakness and limitations.
•Methodologies and models for the security risk assessment of facilities that handle hazardous chemicals Since 2002 is reviewed.•Issues and gaps in the security risk methods and models are identified and presented.•Areas of application of various security risk methods and models were discussed.•Recommendations and future scope of research in the field of security risk is suggested.
Many security risk assessment models have been proposed to describe and analyze security risks and their dependencies in network systems by means of graphs. However, these models suffer from two ...significant problems. First, they require a lot of human intervention and expertise in the graph generation process because they assume that experts are responsible for collecting and organizing large amounts of input data necessary for the assessment. Second, they are difficult to apply to large-scale networks since the graph size and the computational cost grow explosively with the network size. To tackle these problems, we propose a novel methodology named malicious communication dependency analysis (Malcoda) for assessing security risks of enterprise networks. Malcoda identifies risks in a network on the basis of input data automatically obtained from existing security products and describes probabilistic dependencies among information assets, threats, and vulnerabilities through a Bayesian network (BN)-based model dubbed the Malco directed acyclic graph (DAG). It then analyzes the Malco DAG to calculate the probability that each asset and vulnerability is exposed to threats (risk probability). Malcoda minimizes human intervention and enables administrators with limited expertise to easily assess security risks by automatically collecting and organizing the input data required for constructing the graphs. The Malco DAG, which is lighter than existing models, significantly reduces the computational cost and improves the scalability. The evaluation of Malcoda implemented in a virtual enterprise network demonstrates that Malcoda can automatically and quickly complete the assessment process and output reasonable risk probabilities reflecting threats, i.e., intrusion detection system (IDS) alerts. The computational complexity of Malcoda is also found to be less than or equal to that of existing models.
Consumer adoption of mobile shopping apps is an emerging area in m-commerce which poses an interesting challenge for retailers and app developers. In this study, we adapt the Unified Theory of ...Acceptance and Use of Technology 2 (UTAUT2) to investigate factors predicting consumer behavioral intention (BI) and use behavior (UB) towards mobile shopping apps, considering the impact of two manifestations of consumer's perceived risk: Privacy Risk and Security Risk. Because cultural characteristics may moderate the impact of these risks on behavioral intention and use behavior, we conduct two studies from two consumer panels from countries with significant difference in technology use as captured by the Computer-Based Media Support Index (CMSI), namely India (high CMSI) and USA (low CMSI). For both countries, the baseline UTAUT 2 constructs predict the Behavioral Intention to use mobile shopping apps (and subsequently use behavior). However, the manifestations of perceived risk are significant only for the country with the highest CMSI score, suggesting that cultural influences play a strong role in the adoption of m-shopping. Our study has practical implications for theory as it poses the use of m-shopping apps in a cross-cultural context, suggesting that privacy and security moderate intention to use differently across cultures as predicted by the CMSI. From that perspective, it also has practical implications for consumer behavior researchers and app developers challenged with app localization as well as retailers designing mobile shopping apps for an intercultural audience.
•The suitability of UTAUT2 on explaining adoption of m-shopping apps is examined.•Perceived Privacy and Security risks are added to UTAUT2.•We conduct two studies in India and USA using consumer panels.•We find that perceived risks are affecting m-shopping app adoption in India.•Results add to the discussion of adoption stages for developed vs emerging markets.
As intentional attacks to industry have been on the rise in the last years, researchers and institutions put effort in addressing risks of industrial assets exposed to acts of interference. One of ...the key steps of security risk assessment is the evaluation of the attractiveness, i.e. determining which installation or part of it could be of interest to a potential attacker. As security concerns are intrinsically tied to human intention, attractiveness does not only depend on technical characteristics of the facility, but also on the type of threat and its geographic, economic, and socio-political context. Therefore, interdisciplinarity is among the key features of a team tasked with assessing attractiveness. This work is the result of the joint effort of Physical Sciences and Engineering experts and Social Sciences and Humanities experts, and it presents a methodology for the assessment of attractiveness of process facilities to physical terroristic attacks developed using a “terrorist thinking” approach. Technical factors such as plant layout and physical protection systems were combined with modern criminology principles (namely Situational Crime Prevention, i.e. how actors take advantage of situated opportunities to commit a crime) to obtain a comprehensive picture of the possible motives behind a physical terroristic attack to a chemical and process facility (meant as facilities where chemical substances are present and where chemical and/or physical processes occurs). The methodology was applied to a case study featuring facilities located in a critical context; a ranking among facilities was obtained, and the robustness of the results was tested through a Monte Carlo-based uncertainty analysis. The results revealed that it is not possible to obtain a clear ranking of critical facilities accounting only for technical or non-technical factors, but both are necessary. The method developed was demonstrated easy to apply and could be used not only by plant security managers, but also by Institutions and Governments to prioritize critical assets in threatening contexts.
•Interdisciplinary method to assess attractiveness of industrial sites to terrorism.•Past terroristic attacks, geo-political, socio-economic drivers are considered.•Semi-quantitative approach allowing a ranking of the attractiveness of targets.•Application to a case study where terrorism is rooted.•Results highlighted the role of non-technical factors in determining attractiveness.
Chemical process industries (CPIs) face significant safety and security risks that are closely intertwined. However, previous research has predominantly examined these risks separately, lacking a ...comprehensive scientific approach to simultaneously analyze safety and security in critical systems. This research aims to propose an integrated approach to assess safety and security risks in CPIs. To achieve this, a taxonomy of safety and security risk factors consisting of four dimensions (i.e., occurrence probability, severity, vulnerability, and securing) and their respective twenty contributing factors has been developed. The validity and reliability of the taxonomy were assessed using the Delphi method, involving Subject Matter Experts (N = 25), and through statistical analysis. Subsequently, the Fuzzy Analytical Hierarchy Process (FAHP) was employed to determine the importance level of each contributing factor and dimension, thereby enabling the integration of safety and security risk levels. The proposed approach was validated through reality checks, and independent peer review. The findings of this study highlight the dimensions and contributing factors that have the most significant impact on the integrated safety and security risk level. Moreover, the approach provides insights into effectively assigning countermeasures to establish a safe and resilient operation in CPIs. By adopting this integrated assessment approach, CPIs can gain a deeper understanding of the interplay between safety and security risks, allowing for more informed decision-making and the implementation of targeted risk mitigation strategies.
•Chemical threats present a formidable peril to both human well-being and the environment, garnering intensified concern and scrutiny in recent times.•This study proposed a comprehensive taxonomy of safety and security risks in Chemical Process Industries (CPIs).•The CPDI's structured framework enables organizations to systematically evaluate their vulnerabilities, and implement effective risk management strategies.•By adopting this integrated assessment approach, CPIs can gain a deeper understanding of the interplay between safety and security risks.
•With the continuous development of artificial intelligence, machine learning, as an indispensable means to realize artificial intelligence, is constantly improving, and deep learning is one of the ...contents. This article aims to evaluate and warn the security risks of large-scale group activities based on the random forest algorithm.•In this paper, the computational random forest algorithm is used to calculate the importance of variables and the security risk index weight, and combined with the model parameters of the random forest algorithm, optimization experiments and random forest model training experiments are carried out respectively. At the same time, an international youth environmental protection festival is taken as an example to analyze, which has verified the feasibility and effectiveness of this article.•This article mainly evaluates the risks in large-scale group activities, but it can be further improved in future applications. On the basis of it, if the activities want to achieve better results, they must also satisfy the people who participate in the activities. Thereby, it can better help resolve some unnecessary risks and ensure the safety of people in their activities.
With the continuous development of artificial intelligence, machine learning, the necessary way to achieve artificial intelligence, is also constantly improving, of which deep learning is one of the contents. The purpose of this paper is to evaluate and warn the security risk of large-scale group activities based on the random forest algorithm. This paper uses the methods of calculating the importance of the random forest algorithm to variables and the calculation formula of the weight of the security risk index, and combining the model parameters of the random forest algorithm The optimization experiment and the random forest model training experiment are used for risk analysis, and the classification accuracy rate reaches a maximum of 0.86, which leads to the conclusion that the random forest algorithm has good predictive ability in the risk assessment of large-scale group activities. This article takes a certain international youth environmental protection festival as an example for analysis, and better verifies the feasibility and effectiveness of this article.
Abstract The process of attack and defence of side channel attack can be regarded as the process of mutual information game, the two sides of the game are the cryptographic device designer (defence) ...and the enemy. The game goal of the defender is to reduce the local and global risks caused by side channel leakage by formulating relevant defence strategies; For the enemy, the goal of the game is just the opposite. From the perspective of making security strategy and reducing security risk, the mutual information game theory is introduced into the decision-making process of crypto chip designers (defenders) and enemies, and the influence of the choice of offensive and defensive strategy on security risk is investigated.
China is currently the largest energy-consuming nation; however, its contribution to renewable energy investment (REI) is significant and warrants examination. Many studies have analyzed how various ...factors may contribute to REI. However, the roles of environmental higher education (EHE), formal finance (FF), and energy security risk (ESR) in determining REI has not been sufficiently investigated. This analysis is an effort to examine the nexus between EHE, FF, ESR, and REI in China at the aggregate and disaggregate levels from 1996 to 2022. This study employed the autoregressive distributed lag (ARDL) and quantile autoregressive distributed lag (QARDL) models. The results indicate FF, EHE, and ESR effectively stimulate long-run aggregate REI. However, at the disaggregate level, FF significantly escalates investments in solar, wind, geothermal, and hydro energies. At the same time, EHE promotes investments in solar, wind, and hydro energies, and ESRs cause investments in solar and wind energies to grow. The QARDL model confirmed that FF, EHE, and ESR promote REI across most quantiles in the long run. Therefore, it is recommended that policymakers integrate these factors into REI policies.
PDF
