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

Autor: Jean-Luc Grimault, Tanguy Godquin, Jean-Marie Le Bars, Morgan Barbier, Chrystel Gaber
Přispěvatelé: Equipe SAFE - Laboratoire GREYC - UMR6072, Groupe de Recherche en Informatique, Image et Instrumentation de Caen (GREYC), Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU)-Normandie Université (NU)-Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Centre National de la Recherche Scientifique (CNRS)-École Nationale Supérieure d'Ingénieurs de Caen (ENSICAEN), Normandie Université (NU), Orange Labs [Caen], Orange Labs, Godquin, Tanguy
Jazyk: angličtina
Rok vydání: 2019
Předmět:
Zdroj: 38th IEEE International Performance Computing and Communications Conference (IPCCC 2019)
38th IEEE International Performance Computing and Communications Conference (IPCCC 2019), Oct 2019, London, United Kingdom
IPCCC
Popis: International audience; 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.
Databáze: OpenAIRE