Risk Analysis using Monte Carlo Simulation and Bayesian Networks

2006 ◽  
Author(s):  
Claudio Flores ◽  
Fernando Makiyama ◽  
Silvia Nassar ◽  
Paulo Freitas ◽  
Carlos Jacinto
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Risk Analysis ◽  
Bayesian Networks

Risk Analysis by Monte Carlo Simulation over Large Offshore Projects

2021 ◽  
Author(s):  
Agostino Bruzzone ◽  
Kirill Sinelshchikov ◽  
Federico Tarone ◽  
Federica Grosso
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Risk Analysis

A Weighted Monte Carlo Simulation Approach to Risk Assessment of Information Security Management System

2015 ◽  
Vol 11 (4) ◽  
pp. 63-78 ◽  
Author(s):  
Seyed Mojtaba Hosseini Bamakan ◽  
Mohammad Dehghanimohammadabadi
Keyword(s):  
Risk Assessment ◽  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Information Security ◽  
Risk Analysis ◽  
Management System ◽  
Security Management ◽  
International Standards ◽  
Information Security Management ◽  
Information Security Management System

In recent decades, information has become a critical asset to various organizations, hence identifying and preventing the loss of information are becoming competitive advantages for firms. Many international standards have been developed to help organizations to maintain their competitiveness by applying risk assessment and information security management system and keep risk level as low as possible. This study aims to propose a new quantitative risk analysis and assessment methodology which is based on AHP and Monte Carlo simulation. In this method, AHP is used to create favorable weights for Confidentiality, Integrity and Availability (CIA) as security characteristic of any information asset. To deal with the uncertain nature of vulnerabilities and threats, Monte Carlo simulation is utilized to handle the stochastic nature of risk assessment by taking into account multiple judges' opinions. The proposed methodology is suitable for organizations that require risk analysis to implement ISO/IEC 27001 standard.

Gas Turbine Safety Improvement Through Risk Analysis

1988 ◽  
Vol 110 (2) ◽  
pp. 265-270 ◽  
Author(s):  
T. M. Crosby ◽  
G. L. Reinman
Keyword(s):  
Monte Carlo Simulation ◽  
Monte Carlo ◽  
Risk Analysis ◽  
Weibull Distribution ◽  
Gas Turbine ◽  
System Model ◽  
Weibull Analysis ◽  
System Safety ◽  
Weibull Plot ◽  
Safety Improvement

This paper is intended to provide the engineer with the information necessary to understand certain statistical methods that are used to improve system safety. It will provide an understanding of Weibull analysis, in that it describes when the Weibull distribution is appropriate, how to construct a Weibull plot, and how to use the parameters of the Weibull distribution to calculate risk. The paper will also provide the engineer with a comprehension of Monte Carlo simulation as it relates to quantifying safety risk. The basic components of Monte Carlo simulation are discussed as well as the formulation of a system model and its application in the gas turbine industry.

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