DDRIG in DRMS: Multi-target Technology Deployment and Information Disclosure in Attacker-defender Settings: Analyzing Game-theoretic Prescriptions and Human Decisions
DDRIG in DRMS: Multi-target Technology Deployment and Information Disclosure in Attacker-defender Settings: Analyzing Game-theoretic Prescriptions and Human Decisions
批准号:
2215097
负责人:
Jun Zhuang
金额:
$1.53万
依托单位:
依托单位国家:
美国
项目类别:
Standard Grant
财政年份:
2022
资助国家:
美国
项目状态:
已结题
起止时间:
2022-08-01 至 2023-07-31
中文摘要
防御敌对威胁一直是世界各国政府长期关注的中心问题。提高防御能力的一个突出方法是在感兴趣的场所(例如,机场的金属探测器)。在部署新的安全和国防技术时,各机构必须决定如何向公众发布相关信息。鉴于恐怖组织等对手可以获取公开传播的信息,了解发布不同类型信息的影响至关重要。例如,安全机构可以选择仅发布关于部署新技术的场所的子集的信息,从而为对手造成关于在其他场所部署技术的不确定性(例如,机场)。本研究旨在解决这一困难的信息披露问题,通过建立在博弈论和对抗性决策的先前工作,开发模型和实验,为防御性信息披露,对抗性信念和对抗性目标选择决策提供见解。并在安全和防御的背景下稳健地分析技术部署和信息披露策略。为了实现这些目标,本项目开发和分析了一种新的博弈论信号模型,该模型为最佳信息披露策略提供了有见地的分析。此外,人类实验-旨在模仿游戏模型-进行(i)在这种情况下研究人类的信念和决策,(ii)比较游戏理论的处方与实际的人类决策。该项目的成功完成有助于为安全和国防部门技术部署的长期有效性提供信息。虽然这项研究的动机是安全和防御的问题,数学模型和实验框架是推广到任何应用程序,其中的战略发布信息在多个地点是感兴趣的。这个奖项反映了NSF的法定使命,并已被认为是值得支持的评估使用基金会的智力价值和更广泛的影响审查标准。
英文摘要
Defending against adversarial threats has been a central and longstanding focus for governments throughout the world. One prominent approach to improve defensive capabilities is to deploy new technologies among venues of interest (e.g., metal detectors at airports). When it comes to deploying new security and defense technologies, agencies must decide how the related information should be released to the public. Given that adversaries, such as terrorist organizations, can access information that is publicly disseminated, it is critical to understand the implications of releasing different types of information. For instance, security agencies may choose to release information on only a subset of venues where new technology is deployed, creating an uncertainty for an adversary regarding the deployment of the technology at other venues (e.g., airports). This research addresses this difficult information disclosure problem by building on previous work in game theory and adversarial decision making to develop models and experiments that provide insights into defensive information disclosure, adversarial beliefs, and adversarial target selection decisions.The research objectives of this proposed effort are to mathematically model, experimentally test, and robustly analyze technology deployment and information disclosure strategies in the context of security and defense. To meet these objectives, this project develops and analyzes a novel game-theoretic signaling model, which provides insightful analyses into optimal information disclosure strategies. Further, human experiments –designed to mimic the game model – are conducted to (i) study human beliefs and decision making in this context, and (ii) compare the game-theoretic prescriptions with actual human decisions. Successful completion of this project helps to inform the long-term effectiveness of technology deployments within the security and defense sectors. Although this research is motivated by problems in security and defense, the mathematical model and experimental framework is generalizable to any application in which the strategic release of information across multiple venues is of interest.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.
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