Security scheduling for real-world networks

  • Authors:

  • Manish Jain;Vincent Conitzer;Milind Tambe

  • Affiliations:

  • University of Southern California, Los Angeles, CA, USA;Duke University, Durham, NC, USA;University of Southern California, Los Angeles, CA, USA

  • Venue:
  • Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
  • Year:
  • 2013

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Abstract

Network based security games, where a defender strategically places security measures on the edges of a graph to protect against an adversary, who chooses a path through a graph is an important research problem with potential for real-world impact. For example, police forces face the problem of placing checkpoints on roads to inspect vehicular traffic in their day-to-day operations, a security measure the Mumbai police have performed since the terrorist attacks in 2008. Algorithms for solving such network-based security problems have been proposed in the literature, but none of them scale up to solving problems of the size of real-world networks. In this paper, we present Snares, a novel algorithm that computes optimal solutions for both the defender and the attacker in such network security problems. Based on a double-oracle framework, Snares makes novel use of two approaches: warm starts and greedy responses. It makes the following contributions: (1) It defines and uses mincut-fanout, a novel method for efficient warm-starting of the computation; (2) It exploits the sub-modularity property of the defender optimization in a greedy heuristic, which is used to generate "better-responses"; Snares} also uses a better-response computation for the attacker. Furthermore, we evaluate the performance of Snares in real-world networks illustrating a significant advance: whereas state-of-the-art algorithms could handle just the southern tip of Mumbai, {\sc Snares} can compute optimal strategy for the entire urban road network of Mumbai.