Information Risk Management Research Articles

A systematic review examining the use of media as an offence-related behaviour in recidivism of offenders

Risk of harm to others is largely assessed by official behaviours and what an offender conveys to professionals. Recording offence-related behaviour (OB) may assist in high-risk offender management. The extant research on links between media use and violence often involves the general population where real-world offending behaviours are not outcome measures. This systematic review aimed to examine, systematically and critically, research relating to media OB of offenders. Eleven databases were queried to identify relevant literature. To ensure no past and ongoing studies were excluded, key papers' reference lists were closely examined for further relevant studies and experts in the field were contacted. Studies included were assessed for quality across prognostic factors. Three studies were identified as investigating media OB for people who have recidivated. Data synthesis highlighted that different forms of media are used in the process and act of re-offending. Risk level of offenders and media type were factors in recidivism. Among some offenders media OB may be a pathway to re-offending. The recording, monitoring, and open discussion of media OB may inform risk management strategies for offenders. Further prospective research is required which examines media OB and recidivism utilising both qualitative and quantitative methods.

Characterising populations living close to intensive farming and composting facilities in England

Bioaerosol exposure has been linked to adverse respiratory conditions. Intensive farming and composting facilities are important anthropogenic sources of bioaerosols. We aimed to characterise populations living close to intensive farming and composting facilities. We also infer whether the public are becoming more concerned about anthropogenic bioaerosol emissions, using reports of air pollution related incidents attributed to facilities. We mapped the location of 1,257 intensive farming and 310 composting facilities in England in relation to the resident population and its characteristics (sex and age), area characteristics (deprivation proxy and rural/urban classification) and school locations stratified by pre-defined distance bands from these bioaerosol sources. We also calculated the average number of air pollution related incidents per year per facility. We found that more than 16% of the population and 15% of schools are located within 4,828 m of an intensive farming facility or 4,000 m of a composting facility; few people (0.01 %) live very close to these sites and tend to be older people. Close to composting facilities, populations are more likely to be urban and more deprived. The number of incidents were attributed to a small proportion of facilities; population characteristics around these facilities were similar. Results indicate that populations living near composting facilities (particularly>250 to ⩽ 4,000 m) are mostly located in urban areas (80%–88% of the population), which supports the need for more community health studies to be conducted. Results could also be used to inform risk management strategies at facilities with higher numbers of incidents.

Media security of megascience projects: legal experts training

The article discusses the problems of legal experts training to ensure the effective functioning of global research infrastructures (megascience projects) in the context of information-worldview security of media (including Internet communication). The activity of legal experts in the field of megascience projects implies risk management of media security within which the ranking of media waves and the prevention of illegal speech actions are carried out. The work of a legal expert in the field of media security is greatly interdisciplinary and requires exclusively developed management skills. This specialist acts precisely within the framework of information risk management coordinating and moderating the work of the organization’s structural units. A highly qualified specialist in this area, in addition to fundamental legal knowledge, should also possess creative, heuristic expert thinking, be able to analyze, generalize, screen out and differentiate incoming information in the media stream. It is vital for the objective legal-linguistic examination of defamatory, fake and extremist-terrorist discourse. The basis for the formation of such an expert thinking can be the provisions of forensic expertology as a synthetic legal science that studies the patterns of using special knowledge in legal proceedings. The developments in the field of forensic speech science (which studies speech traces of offenses in the media sphere) are particularly valuable for the training of lawyers in the field of media security. The authors consider the classification of speech offenses against media security of megascience projects and justify that legal education in the megascience field is the training of a wide-profile specialist who is able to apply deep legal and linguistic knowledge in a progressively increasing set of situations and experiences, challenges and threats to media security of megascience projects; who can easily adapt; who is ready to acquire new competencies, learn and grow, find his/her own place in a rapidly changing world.

Information Security Risk Analysis Methods for Healthcare Systems

Information and risk analysis in healthcare system is an important issue in the modern technological growth. There are many systems implemented for information security and risk management for information protection. Proper guidance is needed to select the system as all the systems concentrate on information security of healthcare system. The information threats and risk are increasing, and all the issues are integrated to the vulnerabilities producing risk for the healthcare security. The healthcare system process structure and variation are advocated, in which operating performance indication is based on risk scaling factor so that dynamic information security risk analysis is needed. This paper is proposed for information security risk analysis in which the resources, risk threats, vulnerabilities that control the healthcare system. The paper compares the various inputs and outputs are needed by different systems of information security risk assessment and analysis that accurately presents the information security risk. At present, large number of information security risk analysis methodologies are present in the worldwide. Important and efficient methodologies are considered for comparison and quantitative purpose to choose most suitable methodology for healthcare system.

Integrating Exposure and Effect Distributions with the Ecotoxicity Risk Calculator: Case Studies with Crop Protection Products.

ABSTRACTRisk curves describe the relationship between cumulative probability and magnitude of effect and thus express far more information than risk quotients. However, their adoption has remained limited in ecological risk assessment. Therefore, we developed the Ecotoxicity Risk Calculator (ERC) to simplify the derivation of risk curves, which can be used to inform risk management decisions. Case studies are presented with crop protection products, highlighting the utility of the ERC at incorporating various data sources, including surface water modeling estimates, monitoring observations, and species sensitivity distributions. Integr Environ Assess Manag 2021;17:321–330. © 2020 Syngenta Crop Protection, LLC. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC)

Research Design of Mobile Based Decision Support for Early Flood Warning System

Flooding has become one of the most rapidly growing types of natural disaster that has spread around the globe. It is is one of the major natural hazards in many countries and mostly affected in the low-lying or flood prone areas. In order to minimize loss of life and economic losses, a detailed and comprehensive decision making tool is necessary for both flood control planning and emergency service operations. In this paper, we demonstrate our research design for mobile based decision support of Flood Early Warning System (FEWS). We outlined four research objectives. Firstly, critical criteria for flood risk assessment will be identified and the second step will involve develop measurement model for relative flood risk using Geographic Information System (GIS), Multi Attribute Decision Making (MADM) and data mining technique. In the third objectives, the holistic architectural design is develop by incorporating the communication technology and other related ICT requirements for the mobile decision support. The fourth objective is to validate the mathematical model and architectural design. Case study approach is chosen in order to understand the flood event and validate the decision support model. Following well-defined procedures, flood maps were drawn based on the data collected from expert responses to a questionnaire, the field survey, satellite images, and documents from flood management agencies. It is anticipates that by integrating of mathematical model, GIS and mobile application in flood risk assessment could provide useful detailed information for flood risk management, evacuation, communication. The decision support design from this study is perhaps to improve the warning system and contribute to reduction of casualties.

Probabilistic evaluation of loess landslide impact using multivariate model

The Loess Plateau is the largest loess accumulation area around the world, onto which loess landslides have been occurring frequently each year, thus bringing significant threats to communities there. To mitigate or manage the risk brought by loess landslides, many methods have been developed to gain insights into mechanisms that trigger loess landslides, or to identify regions that are susceptible to landslides through landslide susceptibility mapping. However, none of these methods can be used to quantitatively evaluate possible impact of potentially unstable slopes, which offers important information for risk management, especially for regions with high susceptibility to landslides. This study aims to fill this gap by constructing a loess landslide database first from field investigation. Then, a multivariate model for loess landslide data, including its height, width, area, and length, is developed considering correlation among these parameters. Subsequently, the multivariate model is used to predict statistically and quantitatively impact of a potentially unstable loess slope, in terms of slide width, length, and area, given height of the potentially unstable loess slope. The proposed method is applied to loess landslides occurred in Baoji City for illustration. Results show that the proposed method works reasonably well. In addition, some key equations are provided using results from the multivariate model. With these equations, geotechnical engineers or decision-makers can evaluate possible impact of a potentially unstable loess slope with minimal effort.

The Role of the Mechanisms of Information Technology Governance in Activating the Risk Management of Computerized Accounting Information Systems According to (NIST800-37) Framework of Internal Control

This study assesses and analyzes the reality of the mechanisms of information technology governance and risk management of computerized accounting information systems, in addition to testing and analyzing their relationships. It highlights the effect of using the mechanisms of information technology governance in reducing the risks of computerized accounting information systems in business organizations in the Kurdistan Region of Iraq. The aim of this study is to identify the availability of mechanisms of information technology governance in business organizations in the Kurdistan Region, the risks ofcomputerized accounting information systems and how to manage them as well as the inadequacy of controls for the security of these systems.In order to achieve these goals, four main hypotheses are adopted and directed to test the reality of the research variables. The study adopts the descriptive analytical method within the framework of the theoretical presentation of the research and variables, and uses the statistical analysis in writing the practical side of the study. Data is collected through a questionnaire to obtain the opinions of 56 auditors and managers of joint-stock companies in the Kurdistan Region of Iraq.The research reached a set of findings and recommendations, the most prominent of which is that the mechanisms of information technology governance has a role in activating risk management of computerized accounting information technology, and that the mechanisms of information technology governance has an effect on risk management of computerizedaccounting information systems. The most important recommendation is the need for organizations to adopt internal control frameworks related to protecting computerized accounting information systems to protect them from the risks related to them.

The Value of Initial Condition Large Ensembles to Robust Adaptation Decision‐Making

AbstractThe origins of uncertainty in climate projections have major consequences for the scientific and policy decisions made in response to climate change. Internal climate variability, for example, is an inherent uncertainty in the climate system that is undersampled by the multimodel ensembles used in most climate impacts research. Because of this, decision makers are left with the question of whether the range of climate projections across models is due to structural model choices, thus requiring more scientific investment to constrain, or instead is a set of equally plausible outcomes consistent with the same warming world. Similarly, many questions faced by scientists require a clear separation of model uncertainty and that arising from internal variability. With this as motivation and the renewed attention to large ensembles given planning for Phase 7 of the Coupled Model Intercomparison Project (CMIP7), we illustrate the scientific and policy value of the attribution and quantification of uncertainty from initial condition large ensembles, particularly when analyzed in conjunction with multimodel ensembles. We focus on how large ensembles can support regional‐scale robust adaptation decision‐making in ways multimodel ensembles alone cannot. We also acknowledge several recently identified problems associated with large ensembles, namely, that they are (1) resource intensive, (2) redundant, and (3) biased. Despite these challenges, we show, using examples from hydroclimate, how large ensembles provide unique information for the scientific and policy communities and can be analyzed appropriately for regional‐scale climate impacts research to help inform risk management in a warming world.

Analysis of Mangosteen Marketing in Pulau Rambai Village Kampa District Kampar Regency

Mangosteen prices are determined by traders who tend to speculate, causing a weak bargaining position for farmers. Prices are determined unilaterally by traders, making farmers position only as price takers. Mangosteen marketing efficiency analysis needs to be done so that it can discover the cause of the low bargaining power of farmers and price fluctuations and the level of efficiency in each marketing channel. The study aims to analyze the marketing functions, costs, and the marketing efficiency of mangosteen fruit in Pulau Rambai Village, Kampa District, Kampar Regency. The method used is a survey method. Farmer sampling in this study used a simple random sampling method, and as for the traders, samples were taken by census method. The data analysis used is descriptive and quantitative. The results of the study highlight that the marketing functions carried out by each marketing institution are the exchange function, physical function, and facility functions. The exchange function is carried out in the form of a sale and purchase function. Physical functions is performed in the form of packaging, transportation and storage functions. The function of the facilities carried out in the forms of the activities of sorting and grading, financing, risk management, and market information. There are two mangosteen marketing channels in Desa Rambai Island. The most efficient marketing channels are determinedby thecalculation of marketing costs and marketing efficiency. The most efficient chaanel in this study is marketing channel number two.

A spaceborne SAR-based procedure to support the detection of landslides

Abstract. The increasing availability of free-access satellite data represents a relevant opportunity for the analysis and assessment of natural hazards. The systematic acquisition of spaceborne imagery allows for monitoring areas prone to geohydrological disasters, providing relevant information for risk evaluation and management. In cases of major landslide events, for example, spaceborne radar data can provide an effective solution for the detection of slope failures, even in cases with persistent cloud cover. The information about the extension and location of the landslide-affected areas may support decision-making processes during emergency responses. In this paper, we present an automatic procedure based on Sentinel-1 Synthetic Aperture Radar (SAR) images, aimed at facilitating the detection of landslides over wide areas. Specifically, the procedure evaluates changes of radar backscattered signals associated with land cover modifications that may be also caused by mass movements. After a one-time calibration of some parameters, the processing chain is able to automatically execute the download and preprocessing of images, the detection of SAR amplitude changes, and the identification of areas potentially affected by landslides, which are then displayed in a georeferenced map. This map should help decision makers and emergency managers to organize field investigations. The process of automatization is implemented with specific scripts running on a GNU/Linux operating system and exploiting modules of open-source software. We tested the processing chain, in back analysis, on an area of about 3000 km2 in central Papua New Guinea that was struck by a severe seismic sequence in February–March 2018. In the area, we simulated a periodic survey of about 7 months, from 12 November 2017 to 6 June 2018, downloading 36 Sentinel-1 images and performing 17 change detection analyses automatically. The procedure resulted in statistical and graphical evidence of widespread land cover changes that occurred just after the most severe seismic events. Most of the detected changes can be interpreted as mass movements triggered by the seismic shaking.

A real-world information security performance assessment using a multidimensional socio-technical approach.

Measuring the performance of information security is an essential part of the information security management system within organisations. Studies in the past mainly focused on establishing qualitative measurement approaches. Since these can lead to ambiguous conclusions, quantitative metrics are being increasingly proposed as a useful alternative. Nevertheless, the literature on quantitative approaches remains scarce. Thus, studies on the evaluation of information security performance are challenging, especially since many approaches are not tested in organisational settings. The paper aims to validate the model used for evaluating the performance of information security management system through a multidimensional socio-technical approach, in a real-world settings among medium-sized enterprises in Slovenia. The results indicate that information security is strategically defined and compliant, however, measures are primarily implemented at technical and operational levels, while its strategic management remains underdeveloped. We found that the biggest issues are related to information resources and risk management, where information security measurement-related activities proved to be particularly problematic. Even though enterprises do possess certain information security capabilities and are aware of the importance of information security, their current practices make it difficult for them to keep up with the fast-paced technological and security trends.

WFH: Think Before You Click

Reza Alavi MBCS, Chair of BCS IRMA (Information Risk Management and Assurance Group) and Cyber Security & Risk Consultant at Wipro-Cloud looks at getting the cyber basics right when working from home.

Retrospective Assessment of U.S. Army Aviator Anthropometric Screening Process.

INTRODUCTION: The current U.S. Army aviator anthropometric screening process for rotary-wing cockpit compatibility was codified over 30 yr ago. Critical to the process are the anthropometric standards that define what is acceptable for U.S. Army flight school applicants. The purpose of this study was to assess and optimize the efficiency of the standards in screening for anthropometric cockpit compatibility while maintaining safety.METHODS: A retrospective analysis was performed. Anthropometry and disposition data of flight school applicants from 2005 to 2014 were taken from the Aeromedical Electronic Resource Office database to determine efficiency of the process. Data on mishaps from 1972 to 2017 were retrieved from the Risk Management Information System database to determine the safety benchmark of the existing process, to which adjusted standards would be held. Adjustments to standards were modeled that would more efficiently pass applicants over the period studied without exceeding the established acceptable safety level.RESULTS: There were 40,136 (98.28%) applicants who passed the standards, while 702 (1.72%) failed. Most (98.52%) applicants who failed the standards and applied for an anthropometry exception to policy (ETP) received one. The models would pass up to 396 (99.25%) applicants who received ETPs without exceeding the established number of mishaps attributable to the anthropometry standards, which was found to be zero.DISCUSSION: The screening process is efficient and effective, but could be improved. Adjusting the standards could increase process efficiency by passing more applicants during their flight physical and widening the applicant pool, while maintaining the current level of safety.Moczynski AN, Weisenbach CA, McGhee JS. Retrospective assessment of U.S. Army aviator anthropometric screening process. Aerosp Med Hum Perform. 2020; 91(9):725731.

FEATURES AND CONSEQUENCES OF MANIFESTATION OF INFORMATION RISKS AT THE GLOBAL LEVEL IN MODERN CONDITIONS

The article is devoted to the risk analysis associated with the use of information and information technologies. Activation and deployment of “digital transformation programs” are accompanied by the emergence of new or unfamiliar challenges and threats; they have a significant negative impact on all aspects of society and are called as “information risks”. It has been shown that any modern entity with social and economic relations provides a wide range of information risks. The purpose of the research is to identify and substantiate the existing problems of qualitative analysis of the emergence and consequences of global information risks, as well as to develop recommendations for their solution. The analysis of different views according to the problems of global risks has been given. The analysis gives an opportunity to offer a separate group of “global information risks” from a part of global risks. It is shown that this can be determined by: causes and peculiarities of their occurrence and emergence; specific activities in order to reduce the likelihood of their occurrence; exclusion, or mitigation of negative effects of their occurrence; specific requirements for the category, staff and competency of managers who should deal with global information risk management. Recommendations have been offered in order to supplement the existing global risks with a separate group - global information risks and to the list of risks such as “massive fraud and data theft”, “large-scale cyber attacks”, “destruction of critical information infrastructure and networks”. It is necessary to add “global content risks”, “risk of privacy loss (for state and private sectors)”, as well as “risk of confidence loss in the media (sources of information)”. Features of these risks emergence have been considered.

Модель управления информационными рисками социотехнической системы на основе поведенческих особенностей человека

The difficulties associated with the description and prediction of human behavior and its presence in sociotechnical systems (STS) leads to the emergence of a number of specific tasks related to ensuring the information security of STS and its integrity. The article analyzes the general and specific threats to information security that arise in the STS, considers the features of the functioning of sociotechnical systems, and also provides the logic for constructing an information risk management system implemented in the structure of the STS and taking into account behavioral characteristics of a person (goal-setting function), to ensure the safety of information processes in the STS.

A Novel Hybrid CNN-LSTM Scheme for Nitrogen Oxide Emission Prediction in FCC Unit

Fluid Catalytic Cracking (FCC), a key unit for secondary processing of heavy oil, is one of the main pollutant emissions of NOx in refineries which can be harmful for the human health. Owing to its complex behaviour in reaction, product separation, and regeneration, it is difficult to accurately predict NOx emission during FCC process. In this paper, a novel deep learning architecture formed by integrating Convolutional Neural Network (CNN) and Long Short-Term Memory Network (LSTM) for nitrogen oxide emission prediction is proposed and validated. CNN is used to extract features among multidimensional data. LSTM is employed to identify the relationships between different time steps. The data from the Distributed Control System (DCS) in one refinery was used to evaluate the performance of the proposed architecture. The results indicate the effectiveness of CNN-LSTM in handling multidimensional time series datasets with the RMSE of 23.7098, and the R2 of 0.8237. Compared with previous methods (CNN and LSTM), CNN-LSTM overcomes the limitation of high-quality feature dependence and handles large amounts of high-dimensional data with better efficiency and accuracy. The proposed CNN-LSTM scheme would be a beneficial contribution to the accurate and stable prediction of irregular trends for NOx emission from refining industry, providing more reliable information for NOx risk assessment and management.

Application of a unified probabilistic framework to the dose-response assessment of acrolein

BackgroundIn quantitative chemical risk assessment, a reference value is an estimate of an exposure to a chemical that is “likely to be without appreciable risk.” Because current “deterministic” approaches do not quantitatively characterize the likelihood or severity of harm, the National Academies has recommended using reference values derived from a risk-specific dose that are treated as random variables, with probability distributions characterizing uncertainty and variability. ObjectivesIn order to build familiarity and address issues needed for routine and standardized derivation of probabilistic risk-specific dose distributions, a case example applying the unified probabilistic framework presented in Chiu and Slob (2015) is developed for acrolein. This case study is based on an updated systematic evidence map of literature (Keshava et al., 2020) identifying nasal lesions reported in Dorman et al. (2008) as the most appropriate endpoint and study for reference value derivation. MethodsThe probability distribution was calculated for the risk-specific dose, which in this implementation of the approach was calculated for the dose at which 1% of the human population is estimated to experience minimal lesions, and a probabilistic reference value was computed as the 5th percentile of this distribution. A deterministic reference value was also derived for comparison, and a sensitivity analysis of the probabilistic reference value was conducted investigating alternative assumptions for the point of departure type and exposure duration. ResultsThe probabilistic reference value of 6 × 10−4 mg/m3 was slightly lower than the deterministic reference value of 8 × 10−4 mg/m3, and the risk-specific dose distribution had an uncertainty spanning a factor of 137 (95th-5th percentile ratio). Sensitivity analysis yielded slightly higher probabilistic reference values ranging between 9 × 10−4 mg/m3 and 2 × 10−3 mg/m3. ConclusionsUsing a probabilistic approach for deriving a reference value allows quantitative characterization of the severity, incidence, and uncertainty of effects at a given dose. The results can be used to inform risk management decisions and improve risk communication.

Uncertainty propagation of dam break flow using the stochastic non-intrusive B-splines Bézier elements-based method

The non-intrusive B-splines Bézier elements method (BSBEM) is used to perform uncertainty propagation for complex dam break flow models. The predictive efficiency of the BSBEM is first compared to the polynomial chaos expansion (PCE) and Monte Carlo (MC) methods using Stoker’s analytical solution for an idealized dam break flow with discontinuous outputs. The computational efficiency of the proposed methodology is then illustrated by analyzing the uncertainty propagation of a hypothetical failure of an actual dam (Batiscan River) located within the province of Québec (Canada). Three parameters, the input discharge, the Strickler roughness coefficient of the main channel and the average breach width are considered as input random variables from which uncertainties may occur and propagate through the 1D hydraulic numerical model (Mascaret). The obtained results reveal the ability of BSBEM to efficiently predict the statistical moments and probability distributions of the output quantities of interest represented in terms of the downstream discharge, water level and front wave arrival time at different locations of the studied reach, thus yielding useful information for flood risk management with lower computational cost.

Deep transferlearning artificial intelligence accurately stages COVID-19 lung disease severity on portable chest radiographs.

This study employed deep-learning convolutional neural networks to stage lung disease severity of Coronavirus Disease 2019 (COVID-19) infection on portable chest x-ray (CXR) with radiologist score of disease severity as ground truth. This study consisted of 131 portable CXR from 84 COVID-19 patients (51M 55.1±14.9yo; 29F 60.1±14.3yo; 4 missing information). Three expert chest radiologists scored the left and right lung separately based on the degree of opacity (0-3) and geographic extent (0-4). Deep-learning convolutional neural network (CNN) was used to predict lung disease severity scores. Data were split into 80% training and 20% testing datasets. Correlation analysis between AI-predicted versus radiologist scores were analyzed. Comparison was made with traditional and transfer learning. The average opacity score was 2.52 (range: 0-6) with a standard deviation of 0.25 (9.9%) across three readers. The average geographic extent score was 3.42 (range: 0-8) with a standard deviation of 0.57 (16.7%) across three readers. The inter-rater agreement yielded a Fleiss' Kappa of 0.45 for opacity score and 0.71 for extent score. AI-predicted scores strongly correlated with radiologist scores, with the top model yielding a correlation coefficient (R2) of 0.90 (range: 0.73-0.90 for traditional learning and 0.83-0.90 for transfer learning) and a mean absolute error of 8.5% (ranges: 17.2-21.0% and 8.5%-15.5, respectively). Transfer learning generally performed better. In conclusion, deep-learning CNN accurately stages disease severity on portable chest x-ray of COVID-19 lung infection. This approach may prove useful to stage lung disease severity, prognosticate, and predict treatment response and survival, thereby informing risk management and resource allocation.