{"type":"ScholarlyArticle","title":"Comparing Strategic Secrecy and Stackelberg Commitment in Security Games","authors":[{"name":"Qingyu Guo","slug":"qingyu-guo","given":"Qingyu","family":"Guo","affiliation":"Joint NTU-UBC Research Centre of Excellence in Active Living for the Elderly , NTU , Singapore"},{"name":"Bo An","slug":"bo-an","given":"Bo","family":"An","affiliation":"School of Computer Science and Engineering , Nanyang Technological University , Singapore"},{"name":"Branislav Bošanský","slug":"branislav-bosansky","given":"Branislav","family":"Bošanský","affiliation":"Agent Technology Center , Faculty of Electrical Engineering , Czech Technical University in Prague; Department of Computer Science , Aarhus University"},{"name":"Christopher Kiekintveld","slug":"christopher-kiekintveld","given":"Christopher","family":"Kiekintveld","affiliation":"Computer Science Department , University of Texas at El Paso 1 , 2 {qguo005 ,"}],"abstract":"The Strong Stackelberg Equilibrium (SSE) has drawn extensive attention recently in several security domains. However, the SSE concept neglects the advantage of defender's strategic revelation of her private information, and overestimates the observation ability of the adversaries. In this paper, we overcome these restrictions and analyze the tradeoff between strategic secrecy and commitment in security games. We propose a Disguised-resource Security Game (DSG) where the defender strategically disguises some of her resources. We compare strategic information revelation with public commitment and formally show that they have different advantages depending the payoff structure. To compute the Perfect Bayesian Equilibrium (PBE), several novel approaches are provided, including a novel algorithm based on support set enumeration, and an approximation algorithm for \\epsilon-PBE. Extensive experimental evaluation shows that both strategic secrecy and Stackelberg commitment are critical measures in security domain, and our approaches can efficiently solve PBEs for realistic-sized problems.","doi":"10.24963/ijcai.2017/516","url":"https://ijcai.org/proceedings/2017/516","pdf":"https://ijcai.org/proceedings/2017/0516.pdf","markdown":"https://ijcai.org/proceedings/2017/516.md","bibtex":"https://ijcai.org/proceedings/2017/bibtex/516","volume":{"slug":"2017","title":"Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence","short_title":"IJCAI 2017","url":"https://ijcai.org/proceedings/2017/","year":2017,"location":"Melbourne, Australia","dates":"19-25 August 2017","editors":"Carles Sierra","isbn":"978-0-9992411-0-3","publisher":"International Joint Conferences on Artificial Intelligence Organization","doi_prefix":"10.24963/ijcai.2017"},"section":"Multidisciplinary Topics and Applications","track":"Main track","number":516,"pages":{"first":3691,"last":3699},"keywords":["Agent-based and Multi-agent Systems: Noncooperative Games","Multidisciplinary Topics and Applications: AI&Security and Privacy"],"videos":[],"references":[{"position":1,"raw":"[An et al., 2013] Bo An, Matthew Brown, Yevgeniy Vorob- eychik, and Milind Tambe. 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