Placement optimization of IoT security solutions for edge computing based on graph theory

Tanguy Godquin 1, 2 Morgan Barbier 1 Chrystel Gaber 2 Jean-Luc Grimault 2 Jean-Marie Le Bars 1
1 Equipe Monétique & Biométrie - Laboratoire GREYC - UMR6072
GREYC - Groupe de Recherche en Informatique, Image, Automatique et Instrumentation de Caen
Abstract : In this paper, we propose a new method for optimizing the deployment of security solutions within an IoT network. Our approach uses dominating sets and centrality metrics to propose an IoT security framework where security functions are optimally deployed among devices. An example of such a solution is presented based on EndToEnd like encryption. The results reveal overall increased security within the network with minimal impact on the traffic.
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Tanguy Godquin, Morgan Barbier, Chrystel Gaber, Jean-Luc Grimault, Jean-Marie Le Bars. Placement optimization of IoT security solutions for edge computing based on graph theory. 38th IEEE International Performance Computing and Communications Conference (IPCCC 2019), Oct 2019, London, United Kingdom. ⟨hal-02314892⟩

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