Mathematical Model For Risk Assessment Research Articles

Privacy risks of whole-slide image sharing in digital pathology

Access to large volumes of so-called whole-slide images—high-resolution scans of complete pathological slides—has become a cornerstone of the development of novel artificial intelligence methods in pathology for diagnostic use, education/training of pathologists, and research. Nevertheless, a methodology based on risk analysis for evaluating the privacy risks associated with sharing such imaging data and applying the principle “as open as possible and as closed as necessary” is still lacking. In this article, we develop a model for privacy risk analysis for whole-slide images which focuses primarily on identity disclosure attacks, as these are the most important from a regulatory perspective. We introduce a taxonomy of whole-slide images with respect to privacy risks and mathematical model for risk assessment and design . Based on this risk assessment model and the taxonomy, we conduct a series of experiments to demonstrate the risks using real-world imaging data. Finally, we develop guidelines for risk assessment and recommendations for low-risk sharing of whole-slide image data.

A Mathematical Model for Risk Assessment of Social Engineering Attacks

Social engineering is a very common type of malicious activity conducted on cyberspace that targets both individuals and companies in order to gain access to information or systems. It is part of the broader domain of cybersecurity and the first step to mitigate this type of attack is to know its attack vectors. This way, the risk of becoming a victim of this type of attack can be reduced by technical means, proper security culture and procedural solutions – if organizations are referred to.

DETERMINATION OF “WEAK” BY POWER TRANSFORMERS RELIABILITY OF POWER SYSTEMS ACCORDING TO THE RESULTS OF FAILURE RISK ASSESSMENT UNDER EXTERNAL SHORT CIRCUITS

Background. The increase of technological violation intensity and its consequences severity is caused mainly by objectively existing aging and service life depletion of electrical equipment. The power industry liberalization exacerbates the reliable operation problem of the power system and requires identification of power system operation accompanied by the maximum emergency risk with possible cascade accidents development. Therefore, the model development task for assessment of the equipment failure risk based on the diagnostic results of technical condition in particular under short circuit in the external network is relevant today. Objective. The aim of the work is to develop a fuzzy mathematical model for probability assessment of power transformer failure in the presence of a windings defect, short circuit in external network and emergency risk assessment under power transformers out of service. Methods. The fuzzy set theory and fuzzy logic were used for developing a mathematical model of risk assessment of power trans- former failure. The problems of determining the “weak” in terms of power transformers reliability of power systems based on the results of failure risk assessment due to external short circuits were solved by methods of fuzzy logic and probabilistic-statistical simulation of electric power system modes. Results. The necessity of complex simulation of electric power system modes is substantiated for probability assessment of power transformer failure under electrical network disturbances. The simulation of technical condition of power transformer windings was carried out. The short circuit influence on operability level of power transformers of electric power system was investigated. The quantitative indicators of operational risk of electric power system were determined under power transformers out of service. Conclusions. The linguistic mathematical model for estimating the failure probability of power transformer windings in the presence of defect and short circuit in electrical network has been developed to determine the quantitative indicators of emergency risk in power system.

A Mathematical Model for Risk Assessment of Social Engineering Attacks

A Mathematical Model for Risk Assessment of Social Engineering Attacks

Модели оценки риска с функционально различающимися воздействиями на природно-технические системы

Introduction. The complex combination of natural and technogenic factors that lead to dangerous threats to the health and life of the population, as well as to material values, creates a need to develop special mathematical models for risk assessment in the relevant territories. Herewith it is important to take into account the significant differences between these factors. The new areas of research are models that describe natural and technogenic risks using differential equations that reflect different types of functions. The article presents the development of this research area. Goals and objectives. The goal of the article is to create a model for risk assessment in natural and technical systems (PTS), based on taking into account the influences of different natural and technogenic factors on them. Objectives include justification, construction and practical implementation of the mathematical model of risk assessment in the form of differential equations system. Methods include interpretation of the considered influences on PTS in terms of risks and assessment of the dynamic interaction of natural and technogenic factors in the form of inhomogeneous differential equations. Results and discussion. Solutions for models of assessing complex natural and technogenic risks in relation to two cases that differ in NTS are found: functionally different external natural and technogenic influences on PTS, which are understood as their type, in which the effects of both natural and technogenic factors are described by different mathematical functions. Conclusions. The first model considers parabolic (reflecting threats whose intensity gradually decreases with distance from the epicenter) and linear types of influences (reflecting sudden threats). The second model considers parabolic and hyperbolic (reflecting threats, the intensity of which decreases sharply over time) types of influences. It is concluded that it is necessary to create a special computer album of complex influences on the PTS in order to prevent "replay" of various situations and develop the most effective response to emerging dangers from the EMERCOM units and other structures. Key words: model, assessment, natural and technogenic risks, functionally different influences, counteraction, EMERCOM units.

Classifying of Krasnoyarsk territory using a risk-based approach

The problem of sustainable development of industrial territories is considered with using a nonzero risk concept of accidents and catastrophes. Th e mathematical models for risk assessment were chosen for the information system of territorial risk management and safety. The purpose of the work is to identify and analyze basic technological risks for the information system of territorial risk management and safety (IST RMS) of the Krasnoyarsk territory. This information system provides making decision on the implementation of measures aimed at reducing the risks of sustainable development. The following tasks are set in the work: determination of the basic technospheric risks; calculation and analyzing risk of anthropogenic emergencies on the example of the Krasnoyarsk territory; safety analysis of the region. To achieve the purpose of this work were used probabilistic-statistical research methods. The relevance of the work is determined by the need to implement a national safety strategy at the regional level through risk assessment and analysis. The result of the work is an assessment of technological risks and a generalized security analysis of the municipalities and regions in the Krasnoyarsk territory. We obtained the basic development risks and algorithms for assessing territorial safety are determined using statistical analysis, ranges of individual, collective, material and social risks in an anthropogenic emergency. The classifying of territories according to the degree of anthropogenic hazard was carried out. Based on the obtained results, we conclude that in order to achieve acceptable risk values, it is necessary to use an integrated system approach to multifunctional monitoring of territories.

МАТЕМАТИЧНА МОДЕЛЬ ОЦІНКИ РИЗИКУ НЕСАНКЦІОНОВАНОГО ДОСТУПУ ДО ІНФОРМАЦІЇ КОРИСТУВАЧАМИ ІНФОРМАЦІЙНО-ТЕЛЕКОМУНІКАЦІЙНОЇ СИСТЕМИ

The article is devoted to the solution of the actual scientific and practical task – to develop a mathematical model for assessing the risk of unauthorized access to information by users of the information and telecommunication system. Interpretations of such concepts are given: unauthorized access to information, risk and risk assessment used in the course of internal threat research. The characteristics of the user of the information and telecommunication system that affect the value of the probability of unauthorized access to information are determined. It is shown that taking into account the theoretical and practical knowledge of the user of the information and telecommunication system about the characteristics of the physical environment, the computing system, the processed information, which he can use to deliberately violate the rules of demarcation in order to gain unauthorized access to information, will provide a more accurate assessment of this risk. A verification of the adequacy of the developed mathematical model of risk assessment of unauthorized access to information by users of information and telecommunication system with the help of special software is carried out. It is established that the users who have the most experience and experience with information and telecommunication systems (not only in the institution under consideration), the highest level of access to information with restricted access of the institution (organization), occupy responsible positions and are undisciplined are the most likely internal threat of unauthorized access to information. It is the use of a mathematical model for assessing the risk of unauthorized access to information by users of the information and telecommunication system that will improve the comprehensive information protection system of the corresponding information and telecommunication system.

Mathematical model for the evaluation of risk of emergency situations at a dangerous technical object based on artificial neural networks

In the work performed adaptation of artificial neural networks in modern security systems potentially dangerous technical objects — high-rise buildings as tools for assessing and forecasting in management decision. The study obtained the main scientific results: the mathematical model of risk assessment of man-made emergencies based on artificial neural networks; the mathematical model, adapted to the cumulative model of development technogene emergency-fire; provided risk assessment technique manmade emergencies based on artificial neural networks; represented private man-made fire risk assessment methodology using artificial neural networks.

Increasing Certainty of Fault Identification in Power Transformers of Power Plants by Setting Parameters for Fuzzy Model

Проблематика. В умовах об’єктивно існуючого зростання аварійності в сучасних електроенергетичних системах унаслідок відмов потужного силового електрообладнання загострюється проблема забезпечення надійності та безпеки функціонування теплових, атомних і гідроелектростанцій. Тому задача розробки адекватних математичних моделей оцінки технічного стану та визначення ризику відмови силових трансформаторів потужних енергоблоків електростанцій є актуальною. Мета дослідження. Метою роботи є удосконалення нечіткої моделі діагностування технічного стану силового трансформатора настроюванням параметрів та визначення ризику відмови за наявності дефекту. Методика реалізації. При розробці математичної моделі силового трансформатора використовувались підходи, що ґрунтуються на теорії нечітких множин, нечіткої логіки, та методи нелінійної оптимізації. Задача визначення ризику відмови силового трансформатора за наявності дефекту розв’язувалась на основі сформованої ієрархії факторів і параметрів впливу на інтегральний показник ризику відмови силового трансформатора. Результати дослідження. Обґрунтовано необхідність комплексного моделювання технічного стану силового трансформатора і режимів електроенергетичної системи. Удосконалено розроблену нечітку модель оцінки технічного стану силового трансформатора завдяки параметричній ідентифікації оптимальних значень функцій належності нечітких термів лінгвістичних змінних параметрів та визначенню ризику відмови силового трансформатора. Висновки. Для оцінки ризику виникнення аварійних ситуацій в електроенергетичних системах при відмовах електрообладнання запропоновано математичну модель визначення ризику відмови силового трансформатора за наявності дефекту.

MODEL OF INFORMATION TECHNOLOGY PROJECT FINANCING RISK ASSESSMENT

Context. The investigation of the actual problem of information technology mathematical models of risk assessment projects regarding the security of their financing, using fuzzy math to various investment entities is done. Development of this technology will allow adequately review the projects; increase the degree of decisions making validity in case of investments and increase economic security and management. Objective of this work is to develop a mathematical model of fuzzy information technology risk assessment for commercial projects regarding the security of their financing. Method. The two-level fuzzy mathematical model to obtain aggregate risk assessment of the project to combine expert opinions in groups criteria in the final assessment and risk project is designed. The set of criteria for risk assessment projects of different origin, which is divided into groups, is formed. The rules of belonging of the resulting term-evaluation for risk criteria groups for the knowledge base building are formulated. The presented model for risk assessment regarding the security of financing for the project, using a systematic approach based on: fuzzy models of the project evaluation, depending on its origin; fuzzy evaluation model of the industries in which commercial project will be implemented and aggregate risk assessment project valuation. Result. The resulting study is the result of the risk assessment model commercial projects regarding the security of their financing, the release of which is linguistic assessment on the proposed project. The rationality of this assessment show the advantages of the model. Conclusions. The paper solved scientific-practical task of development of a mathematical model of information technology for commercial projects risk assessment regarding the security of their financing. The model project evaluation of different origin in conditions of fuzzy expert evaluations based system of fuzzy sets and fuzzy logic. The practical significance of the results, in particular the developed model for risk assessment regarding the security of funding for the project could be implemented in the work of investment and venture funds. The proposed model is a useful tool for increased safety and validity of investment decision-making entities which wish to finance commercial projects of various origins.

Flood risk assessment model using the fuzzy analytic hierarchy process

Sustainable development and natural disasters are closely interlinked. The impact of catastrophic events on the environment is still very difficult to determine, and such losses are generally underestimated. Development is never neutral in relation to catastrophes: it creates, enhances or reduces the risk of their occurrence. Selection of appropriate methods and mathematical models for risk assessment in relation to the specific features and characteristics of the considered system and available information and resources, is a key parameter of reliability assessment. Numerous authors applied AHP methods with flood risk assessment, but very limited literature is avaliable on the use of fuzzy multiobjective analysis in flood studies. In the recent years, the fuzzy approach for flood risk assessments has gained greater importance. In this paper, we present the fuzzy analytic hierarchy process (FAHP) model for flood risk assessments. Two flood hazard indexes were defined, one based on natural factors and one based on anthropogenic factors. FAHP is applied to data sets to illustrate a model.

Novel fuzzy linguistic based mathematical model to assess risk of invasive alien plant species

The purpose of this study is to develop a mathematical model for risk assessment that evaluates the invasion risk of invasive alien plant species based on their biological attributes. Data for most of the attributes were qualitative and in the form of linguistic terms. In order to handle the numerical and linguistic variables, we proposed three models in the fuzzy environment. In the first model, all the selected attributes were considered as equally important to invasiveness and in the second and third models, these are considered to be unequally important. The important weights for the biological attributes in these models were gathered from the group of experts in plant sciences. Proposed Model III incorporates more sophisticated linguistic tool than Model II. Model II gives better predictions in comparison to the first and third models and it is found to be better tracking system for identifying potential invaders as in the case of conventional risk assessment method.

Model assessment of risk of failure subsystem "man"

There are proposed the method of diagnostics of psychophysiological state of human-operator. There are presented the rationale the choose of informative parameters for evaluation of the psychophysiological state of man. On the basis of the using the mathematical apparatus of fuzzy logic model there are developed by the risk of failure of the subsystem "man" of man-machine system. In the form of a flowchart presents the analysis process incoming to the monitoring/control system, signals (biometric data) about the psychophysical state of the human-operator. One of the parameter groups characterizing the psychophysiological state of human-operator, who, to date, relatively often used in monitoring systems are the parameters of functioning of the human’s body. To assess the risk of failure of the system quantitatively and qualitatively, it is necessary to produce aggregated data collected as part of the tree hierarchy, while aggregation is done in the direction of the arcs of the graph hierarchy. The choice of this group of parameters is due, primarily to the fact that their control is easy to provide the contactless research methods. The latter fact is important, because the current production, as well as in everyday life or in training or competition modes athletes are almost always not possible to attach the sensors directly to the human body. The mathematical description of the calculation of risk, given the uncertainty and inaccuracy of the identification of the factors, the large number of assumptions and estimates, based on the theory of fuzzy sets, and suggests one solution algorithm problems, different in their original parametric data. On the basis of use the mathematical apparatus of fuzzy logic has been developed model for calculating the risk of failure of the subsystem "human" human-machine system. A mathematical model of risk assessment of failure of man-machine system and, consequently, in the future, a computer simulation model for evaluating the risk of failure of the subsystem "Man" can be developed on based of this model

Quantified Risk Ranking Model for Condition-Based Risk and Reliability Centered Maintenance

In the recent past, risk and reliability centered maintenance (RRCM) framework is introduced with a shift in the methodological focus from reliability and probabilities (expected values) to reliability, uncertainty and risk. In this paper authors explain a novel methodology for risk quantification and ranking the critical items for prioritizing the maintenance actions on the basis of condition-based risk and reliability centered maintenance (CBRRCM). The critical items are identified through criticality analysis of RPN values of items of a system and the maintenance significant precipitating factors (MSPF) of items are evaluated. The criticality of risk is assessed using three risk coefficients. The likelihood risk coefficient treats the probability as a fuzzy number. The abstract risk coefficient deduces risk influenced by uncertainty, sensitivity besides other factors. The third risk coefficient is called hazardous risk coefficient, which is due to anticipated hazards which may occur in the future and the risk is deduced from criteria of consequences on safety, environment, maintenance and economic risks with corresponding cost for consequences. The characteristic values of all the three risk coefficients are obtained with a particular test. With few more tests on the system, the values may change significantly within controlling range of each coefficient, hence ‘random number simulation’ is resorted to obtain one distinctive value for each coefficient. The risk coefficients are statistically added to obtain final risk coefficient of each critical item and then the final rankings of critical items are estimated. The prioritization in ranking of critical items using the developed mathematical model for risk assessment shall be useful in optimization of financial losses and timing of maintenance actions.

A mathematical model for risk assessment based on the structure of the air transport of the complex to account for the specifics of air transportation and information system

A mathematical model for risk assessment based on the structure of the air transport complex to account for the specifics of air transportation and information system. Considered aspect of perfection (modernization) of existing system Air Transport lifecycle, which is crucial to ensure effective implementation of innovations in terms of restrictions on the budget development.

English

In this paper authors have discussed risk quantification methods and evaluation of risks and decision parameter to be used for deciding on ranking of the critical items, for prioritization of condition monitoring based risk and reliability centered maintenance (CBRRCM). As time passes any equipment or any product degrades into lower effectiveness and the rate of failure or malfunctioning increases, thereby lowering the reliability. Thus with the passage of time or a number of active tests or periods of work, the reliability of the product or the system, may fall down to a low value known as a threshold value, below which the reliability should not be allowed to dip. Hence, it is necessary to fix up the normal basis for determining the appropriate points in the product life cycle where predictive preventive maintenance may be applied in the programme so that the reliability (the probability of successful functioning) can be enhanced, preferably to its original value, by reducing the failure rate and increasing the mean time between failure. It is very important for defence application where reliability is a prime work. An attempt is made to develop mathematical model for risk assessment and ranking them. Based on likeliness coefficient β1 and risk coefficient β2 ranking of the sub-systems can be modelled and used for CBRRCM. Defence Science Journal, Vol. 64, No. 4, July 2014, pp. 378-384, DOI:http://dx.doi.org/10.14429/dsj.64.6366

Mathematical Modeling and Simulation of Corrosion Processes in Nigerian Crude Oil Pipelines

In this work, a corrosion prediction mathematical model for risk assessment in oil and gas production and transportation facilities has been created. This work focuses on partial pressure of carbon (iv) oxide, CO2 and the operating temperature in process equipment and transportation facility pipes as a function of corrosion rate. The model equation formulated was based on the principle of multiple linear regressions of data. The final model representing the corrosion rate of crude oil equipment was obtained CR = b o + b 1 T + b 2 P (CO 2). The model was simulated using polymath software. The correlation between the experimental and simulated resulted obtained using root mean square deviation (coefficient of determination) was 99.74% which is high, suggesting that the relationship between the predictor and response variables is linear. The variation in the model equation is 0.0066374. This low value of the variance shows that the model is accurate.