Catching Captain Jack: Efficient time and space dependent patrols to combat oil-siphoning in international waters

Publication Type

Conference Proceeding Article

Publication Date

1-2018

Abstract

Pirate syndicates capturing tankers to siphon oil, causing an estimated cost of $5 billion a year, has become a serious security issue for maritime traffic. In response to the threat, coast guards and navies deploy patrol boats to protect international oil trade. However, given the vast area of the sea and the highly time and space dependent behaviors of both players, it remains a significant challenge to find efficient ways to deploy patrol resources. In this paper, we address the research challenges and provide four key contributions. First, we construct a Stackelberg model of the oil-siphoning problem based on incident reports of actual attacks; Second, we propose a compact formulation and a constraint generation algorithm, which tackle the exponentially growth of the defender’s and attacker’s strategy spaces, respectively, to compute efficient strategies of security agencies; Third, to further improve the scalability, we propose an abstraction method, which exploits the intrinsic similarity of defender’s strategy space, to solve extremely large-scale games; Finally, we evaluate our approaches through extensive simulations and a detailed case study with real ship traffic data. The results demonstrate that our approach achieves a dramatic improvement of scalability with modest influence on the solution quality and can scale up to realistic-sized problems.

Keywords

Game theory, Security and Privacy

Discipline

Artificial Intelligence and Robotics | Defense and Security Studies | Numerical Analysis and Scientific Computing

Research Areas

Intelligent Systems and Optimization

Areas of Excellence

Digital transformation

Publication

Proceedings of the 32nd AAAI Conference on Artificial Intelligence, AAAI 2018: New Orleans, February 2-7

First Page

208

Last Page

215

ISBN

9781577358008

Identifier

10.1609/aaai.v32i1.11291

Publisher

AAAI Press

City or Country

Palo Alto, CA

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1609/aaai.v32i1.11291

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