Publications

Abstract not provided.

Abstract not provided.

This paper seeks to explore the conditions where leaders from open democracies to authoritarian states become more or less popular in response to perceived economic and social threats to society, along with increases in societal (economic and social) hardship and group polarization effects. To further explore these conditions, we used a psycho-social approach to develop a preliminary conceptual model of how the perception of threats, changes in societal conditions, and the polarization of society can concurrently influence the popularity of a government leader.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Improved validation for models of complex systems has been a primary focus over the past year for the Resilience in Complex Systems Research Challenge. This document describes a set of research directions that are the result of distilling those ideas into three categories of research -- epistemic uncertainty, strong tests, and value of information. The content of this document can be used to transmit valuable information to future research activities, update the Resilience in Complex Systems Research Challenge's roadmap, inform the upcoming FY18 Laboratory Directed Research and Development (LDRD) call and research proposals, and facilitate collaborations between Sandia and external organizations. The recommended research directions can provide topics for collaborative research, development of proposals, workshops, and other opportunities.

Abstract not provided.

We created a simulation model to investigate potential links between the actions of violent extremist organizations (VEOs), people in the VEO’s home country, and diaspora communities from that country living in the West. We created this model using the DYMATICA framework, which uses a hybrid cognitive system dynamics modeling strategy to simulate behaviors based on psycho-social theory. Initial results of the model are given, focusing on increases to VEO funding and recruiting resulting from an invasion of the VEO’s home country. Western intervention, prejudice, and economic drivers are also considered.

Abstract not provided.

This report contains the written footprint of a Sandia-hosted workshop held in Albuquerque, New Mexico, June 22-23, 2016 on “Complex Systems Models and Their Applications: Towards a New Science of Verification, Validation and Uncertainty Quantification,” as well as of pre-work that fed into the workshop. The workshop’s intent was to explore and begin articulating research opportunities at the intersection between two important Sandia communities: the complex systems (CS) modeling community, and the verification, validation and uncertainty quantification (VVUQ) community The overarching research opportunity (and challenge) that we ultimately hope to address is: how can we quantify the credibility of knowledge gained from complex systems models, knowledge that is often incomplete and interim, but will nonetheless be used, sometimes in real-time, by decision makers?

The Republic of Estonia faced a series of cyber attacks and riots in 2007 that seemed to be highly coordinated and politically motivated, causing short-lived but substantial impact to Estonia's cyber and economic systems. Short-Term harm from these hybrid incidents led to long-Term improvements and leadership by Estonia in the cyber arena. We created a causal model of these attacks to simulate their dynamics. The model uses the DYMATICA framework, a cognitive-system dynamics structure used to quantify and simulate elicited information from subject matter experts. This historical case study underscores how cyber warfare can be a major threat to modern society, and how it can be combined with information operations and kinetic effects to create further disruption. Given states' potential vulnerability to cyber attacks, a deeper understanding of how to analyze, prevent, defend, and utilize the aftermath of these for improvement to systems is critical, as is insight into the fundamental rationale of the outcomes.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

Abstract not provided.

We created a cognition-focused system dynamics model to simulate the dynamics of smoking tendencies based on media influences and communication of opinions. We based this model on the premise that the dynamics of attitudes about smoking can be more deeply understood by combining opinion dynamics with more in-depth psychological models that explicitly explore the root causes of behaviors of interest. Results of the model show the relative effectiveness of two different policies as compared to a baseline: A decrease in advertising spending, and an increase in educational spending. The initial results presented here indicate the utility of this type of simulation for analyzing various policies meant to influence the dynamics of opinions in a population.

Developing nations incur a greater risk to climate change than the developed world due to poorly managed human/natural resources, unreliable infrastructure and brittle governing/economic institutions. These vulnerabilities often give rise to a climate induced “domino effect” of reduced natural resource production-leading to economic hardship, social unrest, and humanitarian crises. Integral to this cascading set of events is increased human migration, leading to the “spillover” of impacts to adjoining areas with even broader impact on global markets and security. Given the complexity of factors influencing human migration and the resultant spill-over effect, quantitative tools are needed to aid policy analysis. Toward this need, a series of migration models were developed along with a system dynamics model of the spillover effect. The migration decision models were structured according to two interacting paths, one that captured long-term “chronic” impacts related to protracted deteriorating quality of life and a second focused on short-term “acute” impacts of disaster and/or conflict. Chronic migration dynamics were modeled for two different cases; one that looked only at emigration but at a national level for the entire world; and a second that looked at both emigration and immigration but focused on a single nation. Model parameterization for each of the migration models was accomplished through regression analysis using decadal data spanning the period 1960-2010. A similar approach was taken with acute migration dynamics except regression analysis utilized annual data sets limited to a shorter time horizon (2001-2013). The system dynamics spillover model was organized around two broad modules, one simulating the decision dynamics of migration and a second module that treats the changing environmental conditions that influence the migration decision. The environmental module informs the migration decision, endogenously simulating interactions/changes in the economy, labor, population, conflict, water, and food. A regional model focused on Mali in western Africa was used as a test case to demonstrate the efficacy of the model.

Abstract not provided.

This project evaluates the effectiveness of moving target defense (MTD) techniques using a new game we have designed, called PLADD, inspired by the game FlipIt [28]. PLADD extends FlipIt by incorporating what we believe are key MTD concepts. We have analyzed PLADD and proven the existence of a defender strategy that pushes a rational attacker out of the game, demonstrated how limited the strategies available to an attacker are in PLADD, and derived analytic expressions for the expected utility of the game’s players in multiple game variants. We have created an algorithm for finding a defender’s optimal PLADD strategy. We show that in the special case of achieving deterrence in PLADD, MTD is not always cost effective and that its optimal deployment may shift abruptly from not using MTD at all to using it as aggressively as possible. We believe our effort provides basic, fundamental insights into the use of MTD, but conclude that a truly practical analysis requires model selection and calibration based on real scenarios and empirical data. We propose several avenues for further inquiry, including (1) agents with adaptive capabilities more reflective of real world adversaries, (2) the presence of multiple, heterogeneous adversaries, (3) computational game theory-based approaches such as coevolution to allow scaling to the real world beyond the limitations of analytical analysis and classical game theory, (4) mapping the game to real-world scenarios, (5) taking player risk into account when designing a strategy (in addition to expected payoff), (6) improving our understanding of the dynamic nature of MTD-inspired games by using a martingale representation, defensive forecasting, and techniques from signal processing, and (7) using adversarial games to develop inherently resilient cyber systems.

Abstract not provided.

Abstract not provided.

Abstract not provided.