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

该项目审查了有组织恐怖团体以外的个人（单独行动者袭击者）针对火车站等公共场所（软目标）的恐怖袭击。 在过去的20年里，这种攻击增加了134%，但单独的攻击-防御模型却没有跟上这一趋势。该项目将开发基于博弈论的新模型，以了解攻击和防御策略，并结合可以验证理论模型的沉浸式模拟。该项目团队拥有运筹学、工业和系统工程、心理学、电气和计算机工程等领域的专业知识。这项工作的实施将有助于国家优先减少关键基础设施及其用户面临的风险。此外，它将为本科生和研究生提供博弈论模型的高级培训。这一科学研究的贡献，从而支持NSF的使命，以促进科学的进步和提高我们的国家福利。在这种情况下，其好处将是改善人为应急管理的见解，这可以在未来的事件中挽救生命。该项目解决了目前对孤独行为者攻击的理解的差距，以指导新的创新防御战略的发展。具体的研究目标是：1）开发和分析攻击和防御策略的博弈论模型以及保护算法，供防御者用于对抗单独行动者攻击者; 2）设计沉浸式模拟以提供描述性代理的行为，并使用风险度量（如预期损害）和不成功攻击的比例来验证博弈论模型。这项研究的智力价值是拓宽了具有不完全信息、多智能体（攻击者和防御者）学习以及部分可观察系统的随机博弈的博弈论知识基础。这是一项变革性的研究，因为它为基础设施安全的风险管理、沉浸式模拟、统计学习和规范行为研究带来了新的视野。该研究的预期结果对应急管理机构、运输安全官员和警察来说既有分析性又有实用性。该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

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.