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ReCAN – Dataset for reverse engineering of Controller Area Networks
This article details the methodology and the approach used to extract and decode the data obtained from the Controller Area Network (CAN) buses in two personal vehicles and three commercial trucks for a total of 36 million data frames. The dataset is composed of two complementary parts, namely the r...
Autores principales: | , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7015990/ https://www.ncbi.nlm.nih.gov/pubmed/32071958 http://dx.doi.org/10.1016/j.dib.2020.105149 |
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author | Zago, Mattia Longari, Stefano Tricarico, Andrea Carminati, Michele Gil Pérez, Manuel Martínez Pérez, Gregorio Zanero, Stefano |
author_facet | Zago, Mattia Longari, Stefano Tricarico, Andrea Carminati, Michele Gil Pérez, Manuel Martínez Pérez, Gregorio Zanero, Stefano |
author_sort | Zago, Mattia |
collection | PubMed |
description | This article details the methodology and the approach used to extract and decode the data obtained from the Controller Area Network (CAN) buses in two personal vehicles and three commercial trucks for a total of 36 million data frames. The dataset is composed of two complementary parts, namely the raw data and the decoded ones. Along with the description of the data, this article also reports both hardware and software requirements to first extract the data from the vehicles and secondly decode the binary data frames to obtain the actual sensors’ data. Finally, to enable analysis reproducibility and future researches, the code snippets that have been described in pseudo-code will be publicly available in a code repository. Motivated enough actors may intercept, interact, and recognize the vehicle data with consumer-grade technology, ultimately refuting, once-again, the security-through-obscurity paradigm used by the automotive manufacturer as a primary defensive countermeasure. |
format | Online Article Text |
id | pubmed-7015990 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-70159902020-02-18 ReCAN – Dataset for reverse engineering of Controller Area Networks Zago, Mattia Longari, Stefano Tricarico, Andrea Carminati, Michele Gil Pérez, Manuel Martínez Pérez, Gregorio Zanero, Stefano Data Brief Engineering This article details the methodology and the approach used to extract and decode the data obtained from the Controller Area Network (CAN) buses in two personal vehicles and three commercial trucks for a total of 36 million data frames. The dataset is composed of two complementary parts, namely the raw data and the decoded ones. Along with the description of the data, this article also reports both hardware and software requirements to first extract the data from the vehicles and secondly decode the binary data frames to obtain the actual sensors’ data. Finally, to enable analysis reproducibility and future researches, the code snippets that have been described in pseudo-code will be publicly available in a code repository. Motivated enough actors may intercept, interact, and recognize the vehicle data with consumer-grade technology, ultimately refuting, once-again, the security-through-obscurity paradigm used by the automotive manufacturer as a primary defensive countermeasure. Elsevier 2020-01-22 /pmc/articles/PMC7015990/ /pubmed/32071958 http://dx.doi.org/10.1016/j.dib.2020.105149 Text en © 2020 The Author(s) http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Engineering Zago, Mattia Longari, Stefano Tricarico, Andrea Carminati, Michele Gil Pérez, Manuel Martínez Pérez, Gregorio Zanero, Stefano ReCAN – Dataset for reverse engineering of Controller Area Networks |
title | ReCAN – Dataset for reverse engineering of Controller Area Networks |
title_full | ReCAN – Dataset for reverse engineering of Controller Area Networks |
title_fullStr | ReCAN – Dataset for reverse engineering of Controller Area Networks |
title_full_unstemmed | ReCAN – Dataset for reverse engineering of Controller Area Networks |
title_short | ReCAN – Dataset for reverse engineering of Controller Area Networks |
title_sort | recan – dataset for reverse engineering of controller area networks |
topic | Engineering |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7015990/ https://www.ncbi.nlm.nih.gov/pubmed/32071958 http://dx.doi.org/10.1016/j.dib.2020.105149 |
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