Petri Net Models of Adversarial Scenarios in Safety and Security

• Activity Number: 146
• Type: Contributed
• Date/Time: Monday, August 10, 2015 : 8:30 AM to 10:20 AM
• Sponsor: Section on Statistics in Defense and National Security
• Author(s): Aparna Huzurbazar* and David Collins
• Companies: Los Alamos National Laboratory and
• Keywords: risk ; attack paths

Abstract

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 stochastic game theory, Markov processes, event graphs, or Bayesian networks, which assume sequential actions, serialized sample paths, or situations static in time. Petri nets, originally developed to model parallelism and concurrency in computer architectures, offer a powerful graphic tool for eliciting scenarios from experts, as well as a basis for simulating scenario outcomes In this paper we describe how generalized stochastic Petri nets can be used for deriving statistical properties of dynamic scenarios involving any number of concurrent actors. We illustrate with an application to site security, implemented using an object-oriented framework for stochastic Petri net simulation developed using the statistical computing language R.