Includes bibliographical references (p. 451-454) and index.
|Statement||Mass Soldal Lund, Bjornar Solhaug, Ketil Stølen|
|Contributions||Solhaug, Bjornar, Stølen, Ketil|
|LC Classifications||HD61 .L86 2010|
|The Physical Object|
|Pagination||xvi, 460 p. :|
|Number of Pages||460|
|LC Control Number||2010936190|
derstanding risks, will in this book ﬁnd guidance on how to conduct a stepwise, structured and systematic analysis and documentation of risks. The book also serves as an introduction to risk analysis in general, and as an in- troduction to the central and well-established underlying concepts and terminology. "This is an awesome book on using Bayesian networks for risk assessment and decision analysis. What makes this book so great is both its content and style. Fenton and Neil explain how the Bayesian networks work and how they can be built and applied to solve various decision-making problems in different s: 6. Risk Analysis A Quantitative Guide Risk and uncertainty are key features of most business and government problems and need to be understood for rational decisions to be made. This book concerns itself with the quantification of risk, the modelling of identified risks and how to make decisions from those models. Our approach involves carrying out a model-driven archi-tectural risk analysis. The process for carrying out this anal-ysis, which is based on that proposed by McGraw, is cen-tred around the creation and analysis of two model-based constructs: architectural patterns and contextualised attack patterns. Once these models are created, these are.
Model-driven risk analysis The CORAS method for model-driven risk analysis oﬀers specialised diagrams to model risks. The CORAS modelling language consists of a graphical and a textual syntax and semantics. It 7. was originally deﬁned as a UML proﬁle, and has later been customised and reﬁned in several. Using Model-Driven Risk Analysis in Component-Based Development: /ch Modular system development causes challenges for security and safety as upgraded sub-components may interact with the system in unforeseen ways. Due to theirCited by: 2. Demonstrates how to carry out predictive risk analysis using a variety of case studies and examples. Written by an experienced expert in the field, in a style suitable for both; industrial and academic audiences. This book is ideal for advanced undergraduates, graduates, analysts and researchers from statistics, engineering, finance, medicine and physical sciences. In this book, Lund, Solhaug and Stølen focus on defensive risk analysis, and more explicitly on a particular approach called CORAS. CORAS is a model-driven method for defensive risk analysis featuring a tool-supported modelling language specially designed to model risks. Their book serves as an introduction to risk analysis in general.
A regular availability risk assessment may be very costly for a company. This thesis presents Model Driven Availability Risk Analysis (MODA), a methodology for identifying, assessing and treating risks to availability of data systems. MODA aims to take one step in the direction of addressing the challenges sketched above and aims for improved. Risk Analysis, published on behalf of the Society for Risk Analysis, is ranked among the top 10 journals in the ISI Journal Citation Reports under the social sciences, mathematical methods category, and provides a focal point for new developments in the field of risk analysis. This international peer-reviewed journal is committed to publishing critical empirical research and . Failure Mode and Effects Analysis (FMEA) is a method designed to: Identify and fully understand potential failure modes and their causes, and the effects of failure on the system or end users, for a given product or process. Assess the risk associated with the identified failure modes, effects and causes, and prioritize issues for. Books shelved as risk-management: Against the Gods: The Remarkable Story of Risk by Peter L. Bernstein, The Black Swan: The Impact of the Highly Improbab.