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Connected Subgraph Defense Games
- Source :
- Algorithmica, 2021, Vol.83(11), pp.3403-3431 [Peer Reviewed Journal], Algorithmic Game Theory. : Springer, pp. 216-236, Lecture Notes in Computer Science, Vol.11801, Algorithmic Game Theory, ALGORITHMICA, Algorithmic Game Theory ISBN: 9783030304720, SAGT
- Publication Year :
- 2021
- Publisher :
- Springer Science and Business Media LLC, 2021.
-
Abstract
- We 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.
- Subjects :
- FOS: Computer and information sciences
TheoryofComputation_MISCELLANEOUS
050101 languages & linguistics
Computer Science::Computer Science and Game Theory
General Computer Science
Computer science
Generalization
Induced subgraph
02 engineering and technology
0102 computer and information sciences
Expected value
01 natural sciences
Combinatorics
symbols.namesake
Computer Science - Computer Science and Game Theory
0502 economics and business
0202 electrical engineering, electronic engineering, information engineering
0501 psychology and cognitive sciences
050207 economics
Special case
Computer Science::Cryptography and Security
Complement (set theory)
Applied Mathematics
Node (networking)
05 social sciences
Tree (graph theory)
Computer Science Applications
010201 computation theory & mathematics
Nash equilibrium
Theory of computation
symbols
020201 artificial intelligence & image processing
Computer Science and Game Theory (cs.GT)
Subjects
Details
- ISBN :
- 978-3-030-30472-0
- ISSN :
- 14320541 and 01784617
- ISBNs :
- 9783030304720
- Volume :
- 83
- Database :
- OpenAIRE
- Journal :
- Algorithmica
- Accession number :
- edsair.doi.dedup.....eabac9e0fe6dbe1d9774868b49b72670