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Tracing Your Smart-Home Devices Conversations: A Real World IoT Traffic Data-Set
Smart-home installations exponential growth has raised major security concerns. To this direction, the GHOST project, a European Union Horizon 2020 Research and Innovation funded project, aims to develop a reference architecture for securing smart-homes IoT ecosystem. It is required to have automate...
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/PMC7698833/ https://www.ncbi.nlm.nih.gov/pubmed/33218082 http://dx.doi.org/10.3390/s20226600 |
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author | Anagnostopoulos, Marios Spathoulas, Georgios Viaño, Brais Augusto-Gonzalez, Javier |
author_facet | Anagnostopoulos, Marios Spathoulas, Georgios Viaño, Brais Augusto-Gonzalez, Javier |
author_sort | Anagnostopoulos, Marios |
collection | PubMed |
description | Smart-home installations exponential growth has raised major security concerns. To this direction, the GHOST project, a European Union Horizon 2020 Research and Innovation funded project, aims to develop a reference architecture for securing smart-homes IoT ecosystem. It is required to have automated and user friendly security mechanisms embedded into smart-home environments, to protect the users’ digital well being. GHOST project aims to fulfill this requirement and one of its main functionalities is the traffic monitoring for all IoT related network protocols. In this paper, the traffic capturing and monitoring mechanism of the GHOST system, called NDFA, is presented, as the first mechanism that is able to monitor smart-home activity in a holistic way. With the help of the NDFA, we compile the GHOST-IoT-data-set, an IoT network traffic data-set, captured in a real world smart-home installation. This data-set contains traffic from multiple network interfaces with both normal real life activity and simulated abnormal functioning of the devices. The GHOST-IoT-data-set is offered to the research community as a proof of concept to demonstrate the ability of the NDFA module to process the raw network traffic from a real world smart-home installation with multiple network interfaces and IoT devices. |
format | Online Article Text |
id | pubmed-7698833 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-76988332020-11-29 Tracing Your Smart-Home Devices Conversations: A Real World IoT Traffic Data-Set Anagnostopoulos, Marios Spathoulas, Georgios Viaño, Brais Augusto-Gonzalez, Javier Sensors (Basel) Article Smart-home installations exponential growth has raised major security concerns. To this direction, the GHOST project, a European Union Horizon 2020 Research and Innovation funded project, aims to develop a reference architecture for securing smart-homes IoT ecosystem. It is required to have automated and user friendly security mechanisms embedded into smart-home environments, to protect the users’ digital well being. GHOST project aims to fulfill this requirement and one of its main functionalities is the traffic monitoring for all IoT related network protocols. In this paper, the traffic capturing and monitoring mechanism of the GHOST system, called NDFA, is presented, as the first mechanism that is able to monitor smart-home activity in a holistic way. With the help of the NDFA, we compile the GHOST-IoT-data-set, an IoT network traffic data-set, captured in a real world smart-home installation. This data-set contains traffic from multiple network interfaces with both normal real life activity and simulated abnormal functioning of the devices. The GHOST-IoT-data-set is offered to the research community as a proof of concept to demonstrate the ability of the NDFA module to process the raw network traffic from a real world smart-home installation with multiple network interfaces and IoT devices. MDPI 2020-11-18 /pmc/articles/PMC7698833/ /pubmed/33218082 http://dx.doi.org/10.3390/s20226600 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 Anagnostopoulos, Marios Spathoulas, Georgios Viaño, Brais Augusto-Gonzalez, Javier Tracing Your Smart-Home Devices Conversations: A Real World IoT Traffic Data-Set |
title | Tracing Your Smart-Home Devices Conversations: A Real World IoT Traffic Data-Set |
title_full | Tracing Your Smart-Home Devices Conversations: A Real World IoT Traffic Data-Set |
title_fullStr | Tracing Your Smart-Home Devices Conversations: A Real World IoT Traffic Data-Set |
title_full_unstemmed | Tracing Your Smart-Home Devices Conversations: A Real World IoT Traffic Data-Set |
title_short | Tracing Your Smart-Home Devices Conversations: A Real World IoT Traffic Data-Set |
title_sort | tracing your smart-home devices conversations: a real world iot traffic data-set |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7698833/ https://www.ncbi.nlm.nih.gov/pubmed/33218082 http://dx.doi.org/10.3390/s20226600 |
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