A General Method for Quantifying Risks Using Probabilistic Graph Models

The method proposed in this paper represents a novel approach where graph-theoretic models used in an analysis rest on a hierarchical network of Modules, each module a model of some subsystem of the overall model.It provides a complete framework for resolving all statistical dependencies and probabilistic uncertainties.In a short series of steps, the method measures the costs, elapsed times, vulnerability scores and the overall risk incurred as a threat - or multiple simultaneous threats - progress through the hierarchy.The method is economical and efficient, consisting of at most 100 network vertices, and requiring an insignificant amount of computation time.Cycles are resolved in a simple and economical manner, requiring the addition of only a single vertex to the network. When a module has too many inputs - violating the "three-input rule" discussed below - the work needed to resolve statistical dependencies grows exponentially. One additional vertex was needed to resolve this conflict.