Decentralized Protection Strategies against SIS Epidemics in Networks

TL;DR

This paper investigates decentralized strategies for protecting networks against SIS epidemic spread, modeling the problem with game theory, analyzing equilibria, and proposing algorithms for optimal protection in complex network structures.

Contribution

It introduces a game-theoretic framework for decentralized protection strategies, analyzes equilibria and efficiency loss, and develops algorithms for multiple community networks.

Findings

Pure and mixed equilibria are characterized for various network topologies.

The Price of Anarchy is quantified, showing efficiency loss in decentralized strategies.

Algorithms are validated through numerical simulations.

Abstract

Defining an optimal protection strategy against viruses, spam propagation or any other kind of contamination process is an important feature for designing new networks and architectures. In this work, we consider decentralized optimal protection strategies when a virus is propagating over a network through a SIS epidemic process. We assume that each node in the network can fully protect itself from infection at a constant cost, or the node can use recovery software, once it is infected. We model our system using a game theoretic framework and find pure, mixed equilibria, and the Price of Anarchy (PoA) in several network topologies. Further, we propose both a decentralized algorithm and an iterative procedure to compute a pure equilibrium in the general case of a multiple communities network. Finally, we evaluate the algorithms and give numerical illustrations of all our results.