Publication Type

Conference Proceeding Article

Version

acceptedVersion

Publication Date

7-2018

Abstract

We consider the problem of allocating scarce security resources among heterogeneous targets to thwart a possible attack. It is well known that deterministic solutions to this problem being highly predictable are severely suboptimal. To mitigate this predictability, the game-theoretic security game model was proposed which randomizes over pure (deterministic) strategies, causing confusion in the adversary. Unfortunately, such mixed strategies typically involve randomizing over a large number of strategies, requiring security personnel to be familiar with numerous protocols, making them hard to operationalize. Motivated by these practical considerations, we propose an easy to use approach for computing strategies that are easy to operationalize and that bridge the gap between the static solution and the optimal mixed strategy. These strategies only randomize over an optimally chosen subset of pure strategies whose cardinality is selected by the defender, enabling them to conveniently tune the trade-off between ease of operationalization and efficiency using a single design parameter. We show that the problem of computing such operationalizable strategies is NP-hard, formulate it as a mixed-integer optimization problem, provide an algorithm for computing epsilon-optimal equilibria, and an efficient heuristic. We evaluate the performance of our approach on the problem of screening for threats at airport checkpoints and show that the Price of Usability, i.e., the loss in optimality to obtain a strategy that is easier to operationalize, is typically not high.

Keywords

Multidisciplinary Topics and Applications, Agent-based and Multi-agent Systems

Discipline

Artificial Intelligence and Robotics | Theory and Algorithms

Research Areas

Intelligent Systems and Optimization

Publication

Proceedings of the Twenty-Seventh International Joint Conference on Artificial Intelligence (IJCAI-18),Stockholm, Sweden, July 13-19

First Page

454

Last Page

460

Identifier

10.24963/ijcai.2018/63

Publisher

IJCAI

City or Country

Menlo Park, CA

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.24963/ijcai.2018/63

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