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Quarantining Malicious IoT Devices in Intelligent Sliced Mobile Networks

The unstoppable adoption of the Internet of Things (IoT) is driven by the deployment of new services that require continuous capture of information from huge populations of sensors, or actuating over a myriad of “smart” objects. Accordingly, next generation networks are being designed to support suc...

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Detalles Bibliográficos
Autores principales: Candal-Ventureira, David, Fondo-Ferreiro, Pablo, Gil-Castiñeira, Felipe, González-Castaño, Francisco Javier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570815/
https://www.ncbi.nlm.nih.gov/pubmed/32899574
http://dx.doi.org/10.3390/s20185054
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author Candal-Ventureira, David
Fondo-Ferreiro, Pablo
Gil-Castiñeira, Felipe
González-Castaño, Francisco Javier
author_facet Candal-Ventureira, David
Fondo-Ferreiro, Pablo
Gil-Castiñeira, Felipe
González-Castaño, Francisco Javier
author_sort Candal-Ventureira, David
collection PubMed
description The unstoppable adoption of the Internet of Things (IoT) is driven by the deployment of new services that require continuous capture of information from huge populations of sensors, or actuating over a myriad of “smart” objects. Accordingly, next generation networks are being designed to support such massive numbers of devices and connections. For example, the 3rd Generation Partnership Project (3GPP) is designing the different 5G releases specifically with IoT in mind. Nevertheless, from a security perspective this scenario is a potential nightmare: the attack surface becomes wider and many IoT nodes do not have enough resources to support advanced security protocols. In fact, security is rarely a priority in their design. Thus, including network-level mechanisms for preventing attacks from malware-infected IoT devices is mandatory to avert further damage. In this paper, we propose a novel Software-Defined Networking (SDN)-based architecture to identify suspicious nodes in 4G or 5G networks and redirect their traffic to a secondary network slice where traffic is analyzed in depth before allowing it reaching its destination. The architecture can be easily integrated in any existing deployment due to its interoperability. By following this approach, we can detect potential threats at an early stage and limit the damage by Distributed Denial of Service (DDoS) attacks originated in IoT devices.
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spelling pubmed-75708152020-10-28 Quarantining Malicious IoT Devices in Intelligent Sliced Mobile Networks Candal-Ventureira, David Fondo-Ferreiro, Pablo Gil-Castiñeira, Felipe González-Castaño, Francisco Javier Sensors (Basel) Article The unstoppable adoption of the Internet of Things (IoT) is driven by the deployment of new services that require continuous capture of information from huge populations of sensors, or actuating over a myriad of “smart” objects. Accordingly, next generation networks are being designed to support such massive numbers of devices and connections. For example, the 3rd Generation Partnership Project (3GPP) is designing the different 5G releases specifically with IoT in mind. Nevertheless, from a security perspective this scenario is a potential nightmare: the attack surface becomes wider and many IoT nodes do not have enough resources to support advanced security protocols. In fact, security is rarely a priority in their design. Thus, including network-level mechanisms for preventing attacks from malware-infected IoT devices is mandatory to avert further damage. In this paper, we propose a novel Software-Defined Networking (SDN)-based architecture to identify suspicious nodes in 4G or 5G networks and redirect their traffic to a secondary network slice where traffic is analyzed in depth before allowing it reaching its destination. The architecture can be easily integrated in any existing deployment due to its interoperability. By following this approach, we can detect potential threats at an early stage and limit the damage by Distributed Denial of Service (DDoS) attacks originated in IoT devices. MDPI 2020-09-05 /pmc/articles/PMC7570815/ /pubmed/32899574 http://dx.doi.org/10.3390/s20185054 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Candal-Ventureira, David
Fondo-Ferreiro, Pablo
Gil-Castiñeira, Felipe
González-Castaño, Francisco Javier
Quarantining Malicious IoT Devices in Intelligent Sliced Mobile Networks
title Quarantining Malicious IoT Devices in Intelligent Sliced Mobile Networks
title_full Quarantining Malicious IoT Devices in Intelligent Sliced Mobile Networks
title_fullStr Quarantining Malicious IoT Devices in Intelligent Sliced Mobile Networks
title_full_unstemmed Quarantining Malicious IoT Devices in Intelligent Sliced Mobile Networks
title_short Quarantining Malicious IoT Devices in Intelligent Sliced Mobile Networks
title_sort quarantining malicious iot devices in intelligent sliced mobile networks
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7570815/
https://www.ncbi.nlm.nih.gov/pubmed/32899574
http://dx.doi.org/10.3390/s20185054
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