Protecting Soft Targets against Lone Actor Attacks using Game Theory and Immersive Simulations

This project examines terrorist attacks by individuals who are outside of an organized terrorist group (lone actor attackers) that target public spaces like train stations (soft targets). Such attacks have increased 134 percent in the last 20 years, yet lone actor attack-defend models have not kept up with the trend. The project will develop new models based on game-theory to understand attack and defense strategies combined with immersive simulations that can validate the theoretical models. The project team has expertise in the fields of operations research, industrial and systems engineering, psychology, and electrical and computer engineering. Implementation of this work will contribute to the national priority to reduce risk to critical infrastructures and their users. Furthermore, it will provide advanced training in game-theoretic models for undergraduate and graduate students. This scientific research contribution thus supports NSF's mission to promote the progress of science and to advance our national welfare. In this case, the benefits will be insights to improve man-made emergency management, which can save lives in future events.

This project addresses the gaps in current understanding of lone actor attacks to guide the development of new innovative defense strategies. Specific research objectives are: 1) to develop and analyze game-theoretic models of attack and defense strategies, and protection algorithms, to be used by the defenders against lone actor attackers; 2) to design immersive simulations to provide descriptive agents' behavior and to validate the game-theoretic models using risk metrics such as expected damage, and the fraction of unsuccessful attacks. The intellectual merit of this research is the broadening of the knowledge base of game theory with incomplete information, multi-agent (attacker and defender) learning, and stochastic games of partially observable systems. This is transformational research since it brings a fresh vision into the risk management, immersive simulations, statistical learning and normative behavior studies for infrastructure security. The anticipated results of this research are both analytical and practical for emergency management agencies, transportation safety officers, and the police.

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.