Petri Net Models of Adversarial Scenarios in Safety and Security

摘要

Adversarial scenarios of interest to the defense and intelligence communities, such as attacks on guarded facilities, involve multiple autonomous actors operating concurrently and interactively. These scenarios cannot be modeled realistically with methods such as Markov processes, stochastic game theory, event graphs, or Bayesian networks, which assume sequential actions, serialized sample paths, or situations static in time. Similar considerations apply in areas such as environmental risk analysis, where actors may be people or natural events, such as earthquakes. Petri nets, originally developed to model concurrency in computer architectures, offer a powerful graphic tool for eliciting scenarios from experts, as well as a basis for simulating scenario outcomes. We describe how stochastic Petri nets can be used to derive statistical properties of dynamic scenarios involving any number of concurrent actors, and illustrate with an application to site security, implemented using the statistical computing language R.