2015
DOI: 10.1109/tcns.2015.2426755
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Decentralized Protection Strategies Against SIS Epidemics in Networks

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 usi… Show more

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Cited by 57 publications
(72 citation statements)
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“…A similar threshold behavior was also obtained in [22] under the NIMFA for specific classes of networks (specifically, complete graphs, complete bipartite graphs and multi-community networks). Our result shows that this property holds under the DBMF approximation in general networks.…”
Section: Properties Of Pure Nash Equilibriumsupporting
confidence: 74%
“…A similar threshold behavior was also obtained in [22] under the NIMFA for specific classes of networks (specifically, complete graphs, complete bipartite graphs and multi-community networks). Our result shows that this property holds under the DBMF approximation in general networks.…”
Section: Properties Of Pure Nash Equilibriumsupporting
confidence: 74%
“…In this sense, our work extends (with virus spread) and generalizes the related work [12], [19], [27]. However, to the best of our knowledge, network formation games concerning virus spread and protection both with or without the performance aspects have not been considered in the NFG framework, although security games [33], [34], [35], [36], [37], [38] have been used in modeling the virus spread suppression and network immunization. Performance aspects, represented by the hopcounts are linearly independent from the resilience to virus spread-the two metrics do not possess closed-form expressions-making the NFG problem challenging, apart from the novelty.…”
Section: Related Workmentioning
confidence: 69%
“…Although we can find a few attempts for this direction in the literature on spreading processes, most of them rely on extensive simulations [28], homogeneity of the contact patterns [29], or homogeneity of node and edge dynamics [30]. This situation is in contrast with the control of epidemic processes over a static networks, for which a plethora of results have been obtained based on game theory [31,32] and convex optimization frameworks [33,34].…”
Section: Heterogeneous Asis Modelmentioning
confidence: 99%