Cargando…

Analytical Modeling for Identification of the Machine Code Architecture of Cyberphysical Devices in Smart Homes

Ensuring the security of modern cyberphysical devices is the most important task of the modern world. The reason for this is that such devices can cause not only informational, but also physical damage. One of the approaches to solving the problem is the static analysis of the machine code of the fi...

Descripción completa

Detalles Bibliográficos
Autores principales: Kotenko, Igor, Izrailov, Konstantin, Buinevich, Mikhail
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8840385/
https://www.ncbi.nlm.nih.gov/pubmed/35161762
http://dx.doi.org/10.3390/s22031017
_version_ 1784650606186594304
author Kotenko, Igor
Izrailov, Konstantin
Buinevich, Mikhail
author_facet Kotenko, Igor
Izrailov, Konstantin
Buinevich, Mikhail
author_sort Kotenko, Igor
collection PubMed
description Ensuring the security of modern cyberphysical devices is the most important task of the modern world. The reason for this is that such devices can cause not only informational, but also physical damage. One of the approaches to solving the problem is the static analysis of the machine code of the firmware of such devices. The situation becomes more complicated in the case of a Smart Home, since its devices can have different processor architectures (means instruction sets). In the case of cyberphysical devices of the Smart Home, the destruction of machine code due to physical influences is also possible. Therefore, the first step is to correctly identify the processor architecture. In the interests of this, a machine code model is proposed that has a formal notation and takes into account the possibility of code destruction. The article describes the full cycle of research (including experiment) in order to obtain this model. The model is based on byte-frequency machine code signatures. The experiment resulted in obtaining template signatures for the Top-16 processor architectures: Alpha, X32, Amd64, Arm64, Hppa64, I486, I686, Ia64, Mips, Mips64, Ppc, Ppc64, RiscV64, S390, S390x and Sparc64.
format Online
Article
Text
id pubmed-8840385
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher MDPI
record_format MEDLINE/PubMed
spelling pubmed-88403852022-02-13 Analytical Modeling for Identification of the Machine Code Architecture of Cyberphysical Devices in Smart Homes Kotenko, Igor Izrailov, Konstantin Buinevich, Mikhail Sensors (Basel) Article Ensuring the security of modern cyberphysical devices is the most important task of the modern world. The reason for this is that such devices can cause not only informational, but also physical damage. One of the approaches to solving the problem is the static analysis of the machine code of the firmware of such devices. The situation becomes more complicated in the case of a Smart Home, since its devices can have different processor architectures (means instruction sets). In the case of cyberphysical devices of the Smart Home, the destruction of machine code due to physical influences is also possible. Therefore, the first step is to correctly identify the processor architecture. In the interests of this, a machine code model is proposed that has a formal notation and takes into account the possibility of code destruction. The article describes the full cycle of research (including experiment) in order to obtain this model. The model is based on byte-frequency machine code signatures. The experiment resulted in obtaining template signatures for the Top-16 processor architectures: Alpha, X32, Amd64, Arm64, Hppa64, I486, I686, Ia64, Mips, Mips64, Ppc, Ppc64, RiscV64, S390, S390x and Sparc64. MDPI 2022-01-28 /pmc/articles/PMC8840385/ /pubmed/35161762 http://dx.doi.org/10.3390/s22031017 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/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 (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Kotenko, Igor
Izrailov, Konstantin
Buinevich, Mikhail
Analytical Modeling for Identification of the Machine Code Architecture of Cyberphysical Devices in Smart Homes
title Analytical Modeling for Identification of the Machine Code Architecture of Cyberphysical Devices in Smart Homes
title_full Analytical Modeling for Identification of the Machine Code Architecture of Cyberphysical Devices in Smart Homes
title_fullStr Analytical Modeling for Identification of the Machine Code Architecture of Cyberphysical Devices in Smart Homes
title_full_unstemmed Analytical Modeling for Identification of the Machine Code Architecture of Cyberphysical Devices in Smart Homes
title_short Analytical Modeling for Identification of the Machine Code Architecture of Cyberphysical Devices in Smart Homes
title_sort analytical modeling for identification of the machine code architecture of cyberphysical devices in smart homes
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8840385/
https://www.ncbi.nlm.nih.gov/pubmed/35161762
http://dx.doi.org/10.3390/s22031017
work_keys_str_mv AT kotenkoigor analyticalmodelingforidentificationofthemachinecodearchitectureofcyberphysicaldevicesinsmarthomes
AT izrailovkonstantin analyticalmodelingforidentificationofthemachinecodearchitectureofcyberphysicaldevicesinsmarthomes
AT buinevichmikhail analyticalmodelingforidentificationofthemachinecodearchitectureofcyberphysicaldevicesinsmarthomes