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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...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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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. |
format | Online Article Text |
id | pubmed-7570815 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
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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