Linear loss function for the network blocking game: An efficient model for measuring network robustness and link criticality

Aron Laszka, Dávid Szeszlér, L. Buttyán

Research output: Chapter in Book/Report/Conference proceedingConference contribution

3 Citations (Scopus)

Abstract

In order to design robust networks, first, one has to be able to measure robustness of network topologies. In [1], a game-theoretic model, the network blocking game, was proposed for this purpose, where a network operator and an attacker interact in a zero-sum game played on a network topology, and the value of the equilibrium payoff in this game is interpreted as a measure of robustness of that topology. The payoff for a given pair of pure strategies is based on a loss-in-value function. Besides measuring the robustness of network topologies, the model can be also used to identify critical edges that are likely to be attacked. Unfortunately, previously proposed loss-in-value functions are either too simplistic or lead to a game whose equilibrium is not known to be computable in polynomial time. In this paper, we propose a new, linear loss-in-value function, which is meaningful and leads to a game whose equilibrium is efficiently computable. Furthermore, we show that the resulting game-theoretic robustness metric is related to the Cheeger constant of the topology graph, which is a well-known metric in graph theory.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages152-170
Number of pages19
Volume7638 LNCS
DOIs
Publication statusPublished - 2012
Event3rd International Conference on Decision and Game Theory for Security, GameSec 2012 - Budapest, Hungary
Duration: Nov 5 2012Nov 6 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7638 LNCS
ISSN (Print)03029743
ISSN (Electronic)16113349

Other

Other3rd International Conference on Decision and Game Theory for Security, GameSec 2012
CountryHungary
CityBudapest
Period11/5/1211/6/12

Fingerprint

Criticality
Loss Function
Linear Function
Topology
Game
Robustness
Network Topology
Value Function
Model
Graph theory
Metric
Zero sum game
Robust Design
Polynomials
Polynomial time
Likely
Graph in graph theory
Operator

Keywords

  • adversarial games
  • blocking games
  • Cheeger constant
  • computational complexity
  • game theory
  • network robustness

ASJC Scopus subject areas

  • Computer Science(all)
  • Theoretical Computer Science

Cite this

Laszka, A., Szeszlér, D., & Buttyán, L. (2012). Linear loss function for the network blocking game: An efficient model for measuring network robustness and link criticality. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 7638 LNCS, pp. 152-170). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7638 LNCS). https://doi.org/10.1007/978-3-642-34266-0_9

Linear loss function for the network blocking game : An efficient model for measuring network robustness and link criticality. / Laszka, Aron; Szeszlér, Dávid; Buttyán, L.

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7638 LNCS 2012. p. 152-170 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 7638 LNCS).

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Laszka, A, Szeszlér, D & Buttyán, L 2012, Linear loss function for the network blocking game: An efficient model for measuring network robustness and link criticality. in Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). vol. 7638 LNCS, Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 7638 LNCS, pp. 152-170, 3rd International Conference on Decision and Game Theory for Security, GameSec 2012, Budapest, Hungary, 11/5/12. https://doi.org/10.1007/978-3-642-34266-0_9
Laszka A, Szeszlér D, Buttyán L. Linear loss function for the network blocking game: An efficient model for measuring network robustness and link criticality. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7638 LNCS. 2012. p. 152-170. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). https://doi.org/10.1007/978-3-642-34266-0_9
Laszka, Aron ; Szeszlér, Dávid ; Buttyán, L. / Linear loss function for the network blocking game : An efficient model for measuring network robustness and link criticality. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 7638 LNCS 2012. pp. 152-170 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).
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