There are a number of attacker models in the area of anonymous communication. Most of them are either very simplified or pretty abstract therefore difficult to generalize or even identify in real networks. While some papers distinct different attacker types, the usual approach is to present an anonymization technique and then to develop an attacker model for it in order to identify properties o...

Computational models are intensively used in engineering for risk analysis or prediction of future outcomes. Uncertainty and sensitivity analyses are of great help in these purposes. Although several methods exist to perform variance-based sensitivity analysis of model output with independent inputs only a few are proposed in the literature in the case of dependent inputs. This is explained by ...

The study and application of risk analysis provides a set of tools with a strong methodological foundation. This chapter describes how risk analysis can be integrated into the intelligence cycle for producing terrorism threat assessments and warnings. Intelligence professionals can use the risk analyst’s toolbox to sharpen conclusions that are made in intelligence products by providing support ...

This paper reviews and discusses some key concept and principles of risk analysis and risk management, based on a set of statements, formulated as myths about risk. Examples of such myths are: risk is equal to the expected value, risk equals uncertainty, risk can be expressed by probabilities, risk is equal to an event, risk acceptance criteria contribute to obtaining a high safety standard, an...

In this paper, we consider the nonconvex minimization problem of the value-at-risk (VaR) that arises from financial risk analysis. By considering this problem as a special linear program with linear complementarity constraints (a bilevel linear program to be more precise), we develop upper and lower bounds for the minimum VaR and show how the combined bounding procedures can be used to compute ...