An Approach for Model Based Risk Assessment 1st Edition by Bjorn Axel Gran, Rune Fredriksen, Atoosa PJ Thunem ISBN 9783540301387

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ISBN 10: 
ISBN 13: 9783540301387
Author: Bjorn Axel Gran, Rune Fredriksen, Atoosa PJ Thunem

Traditional risk analysis and assessment is based on failure-oriented models of the system. In contrast to this, model-based risk assessment (MBRA) utilizes success-oriented models describing all intended system aspects, including functional, operational and organisational aspects of the target. The target models are then used as input sources for complementary risk analysis and assessment techniques, as well as a basis for the documentation of the assessment results. The EU-funded CORAS project developed a tool-supported methodology for model-based risk analysis of security-critical systems. The methodology has been tried out within the telemedicine and e-commerce areas, and provided through a series of seven trials a sound basis for risk assessments. This paper gives an overview of the results with focus on how the approach can be applied for addressing security aspects in a safety critical application and discusses how the methodology can be applied as a part of a trust case development.

An Approach for Model-Based Risk Assessment 1st Table of contents:

• Introduction
  1.1 Motivation and Background
  1.2 Objectives of Model-Based Risk Assessment
  1.3 Key Contributions
  1.4 Structure of the Paper

• Preliminaries
  2.1 Risk Assessment: Definitions and Concepts
  2.2 Model-Based Approaches in Risk Analysis
  2.3 Types of Risk Models: Qualitative and Quantitative
  2.4 Related Work in Risk Assessment Models

• Framework for Model-Based Risk Assessment
  3.1 Overview of the Proposed Framework
  3.2 Key Components of Model-Based Risk Assessment
  3.3 Data Requirements and Model Inputs
  3.4 Integration with Existing Risk Assessment Methods

• Modeling Techniques for Risk Assessment
  4.1 Statistical Models for Risk Prediction
  4.2 Simulation-Based Approaches
  4.3 Decision Trees and Probabilistic Models
  4.4 Machine Learning in Risk Assessment Models

• Risk Assessment Methodology
  5.1 Identification of Risk Factors
  5.2 Risk Estimation and Quantification
  5.3 Sensitivity Analysis and Uncertainty Quantification
  5.4 Validation and Calibration of Models

• Applications of Model-Based Risk Assessment
  6.1 Risk Assessment in Finance and Insurance
  6.2 Health and Safety Risk Assessment
  6.3 Environmental Risk Assessment
  6.4 Risk Assessment in Engineering Systems

• Case Studies and Experimental Results
  7.1 Case Study 1: Financial Risk Modeling
  7.2 Case Study 2: Environmental Risk Assessment
  7.3 Performance Evaluation of the Model-Based Approach
  7.4 Comparison with Traditional Risk Assessment Methods

• Discussion and Future Work
  8.1 Strengths and Limitations of the Approach
  8.2 Potential Improvements in Modeling Techniques
  8.3 Future Directions and Emerging Trends in Risk Assessment

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