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Connected Subgraph Defense Games
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AbstractWe study a security game over a network played between adefenderandkattackers. Every attacker chooses, probabilistically, a node of the network to damage. The defender chooses, probabilistically as well, a connected induced subgraph of the network of$$\lambda $$λnodes to scan and clean. Each attacker wishes to maximize the probability of escaping her cleaning by the defender. On the other hand, the goal of the defender is to maximize the expected number of attackers that she catches. This game is a generalization of the model from the seminal paper of Mavronicolas et al. Mavronicolas et al. (in: International symposium on mathematical foundations of computer science, MFCS, pp 717–728, 2006). We are interested in Nash equilibria of this game, as well as in characterizingdefense-optimalnetworks which allow for the bestequilibrium defense ratio; this is the ratio ofkover the expected number of attackers that the defender catches in equilibrium. We provide a characterization of the Nash equilibria of this game and defense-optimal networks. The equilibrium characterizations allow us to show that even if the attackers are centrally controlled the equilibria of the game remain the same. In addition, we give an algorithm for computing Nash equilibria. Our algorithm requires exponential time in the worst case, but it is polynomial-time for$$\lambda $$λconstantly close to 1 orn. For the special case of tree-networks, we further refine our characterization which allows us to derive a polynomial-time algorithm for deciding whether a tree is defense-optimal and if this is the case it computes a defense-optimal Nash equilibrium. On the other hand, we prove that it is$${\mathtt {NP}}$$NP-hard to find a best-defense strategy if the tree is not defense-optimal. We complement this negative result with a polynomial-time constant-approximation algorithm that computes solutions that are close to optimal ones for general graphs. Finally, we provide asymptotically (almost) tight bounds for thePrice of Defensefor any$$\lambda $$λ; this is the worst equilibrium defense ratio over all graphs.
Springer Science and Business Media LLC
Title: Connected Subgraph Defense Games
Description:
AbstractWe study a security game over a network played between adefenderandkattackers.
Every attacker chooses, probabilistically, a node of the network to damage.
The defender chooses, probabilistically as well, a connected induced subgraph of the network of$$\lambda $$λnodes to scan and clean.
Each attacker wishes to maximize the probability of escaping her cleaning by the defender.
On the other hand, the goal of the defender is to maximize the expected number of attackers that she catches.
This game is a generalization of the model from the seminal paper of Mavronicolas et al.
Mavronicolas et al.
(in: International symposium on mathematical foundations of computer science, MFCS, pp 717–728, 2006).
We are interested in Nash equilibria of this game, as well as in characterizingdefense-optimalnetworks which allow for the bestequilibrium defense ratio; this is the ratio ofkover the expected number of attackers that the defender catches in equilibrium.
We provide a characterization of the Nash equilibria of this game and defense-optimal networks.
The equilibrium characterizations allow us to show that even if the attackers are centrally controlled the equilibria of the game remain the same.
In addition, we give an algorithm for computing Nash equilibria.
Our algorithm requires exponential time in the worst case, but it is polynomial-time for$$\lambda $$λconstantly close to 1 orn.
For the special case of tree-networks, we further refine our characterization which allows us to derive a polynomial-time algorithm for deciding whether a tree is defense-optimal and if this is the case it computes a defense-optimal Nash equilibrium.
On the other hand, we prove that it is$${\mathtt {NP}}$$NP-hard to find a best-defense strategy if the tree is not defense-optimal.
We complement this negative result with a polynomial-time constant-approximation algorithm that computes solutions that are close to optimal ones for general graphs.
Finally, we provide asymptotically (almost) tight bounds for thePrice of Defensefor any$$\lambda $$λ; this is the worst equilibrium defense ratio over all graphs.
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