Information Design for Multiple Interdependent Defenders: Work Less, Pay Off More

Chenghan Zhou, Andrew Spivey, Haifeng Xu () and Thanh H. Nguyen
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Chenghan Zhou: Department of Computer Science, Princeton University, Princeton, NJ 08544, USA
Andrew Spivey: Department of Computer and Information Science, University of Oregon, Eugene, OR 97403, USA
Haifeng Xu: Department of Computer Science and Data Science Institute, University of Chicago, Chicago, IL 60605, USA
Thanh H. Nguyen: Department of Computer and Information Science, University of Oregon, Eugene, OR 97403, USA

Games, 2023, vol. 14, issue 1, 1-18

Abstract: This paper studies the problem of information design in a general security game setting in which multiple self-interested defenders attempt to provide protection simultaneously for the same set of important targets against an unknown attacker. A principal, who can be one of the defenders, has access to certain private information (i.e., attacker type), whereas other defenders do not. We investigate the question of how that principal, with additional private information, can influence the decisions of the defenders by partially and strategically revealing her information. In particular, we develop a polynomial time ellipsoid algorithm to compute an optimal private signaling scheme. Our key finding is that the separation oracle in the ellipsoid approach can be carefully reduced to bipartite matching. Furthermore, we introduce a compact representation of any ex ante persuasive signaling schemes by exploiting intrinsic security resource allocation structures, enabling us to compute an optimal scheme significantly faster. Our experiment results show that by strategically revealing private information, the principal can significantly enhance the protection effectiveness for the targets.

Keywords: information design; security games; persuasion (search for similar items in EconPapers)
JEL-codes: C C7 C70 C71 C72 C73 (search for similar items in EconPapers)
Date: 2023
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