Online Program Home
My Program

Abstract Details

Activity Number: 160 - Quantifying Uncertainty
Type: Topic Contributed
Date/Time: Monday, July 30, 2018 : 10:30 AM to 12:20 PM
Sponsor: Uncertainty Quantification for Complex Systems Interest Group
Abstract #328427 Presentation
Title: Modeling Uncertainty in Physical Security Systems
Author(s): Aparna Huzurbazar*
Companies: Los Alamos National Laboratory
Keywords: adversarial scenarios; Petri net; cyber-physical security

Physical and cyber security systems are an important line of defense for the protection of any property of interest. Scenarios involving intelligent adversaries and their interaction with such systems are of interest to the defense and intelligence communities. These can include, but are not limited to, attacks on guarded facilities that can involve multiple autonomous actors operating concurrently and interactively. A variety of modeling methods can be used such as Bayesian networks, Petri nets, stochastic game theory and event graphs. All of these involve uncertainty of differing types. Uncertainty introduced by cyber-security models is distinct from that in physical security systems, while combined cyber-physical security systems have their own challenges. Additionally, data on cyber security intrusion detection is not easily shareable to an external modeler. Data from physical force-on-force exercises has its own limitations for modelers due to constraints created by the exercise. Simulation tools augmenting these methods create their own set of uncertainties. This talk will discuss these issues and provide an illustration using an application to site security.

Authors who are presenting talks have a * after their name.

Back to the full JSM 2018 program