A dataset of barometric readings for enhancing security and privacy of IoT

<p>The security and privacy of wireless channels is typically enforced by leveraging cryptographic tools. However, there are scenarios where these methods are unfit, such as in resource-constrained environments, i.e., Internet of Things (IoT), or when an extra layer of security is needed. A pr...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Omar Adel Ibrahim (18394779) (author)
مؤلفون آخرون: Gabriele Oligeri (14151426) (author), Roberto Di Pietro (16864155) (author)
منشور في: 2023
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author Omar Adel Ibrahim (18394779)
author2 Gabriele Oligeri (14151426)
Roberto Di Pietro (16864155)
author2_role author
author
author_facet Omar Adel Ibrahim (18394779)
Gabriele Oligeri (14151426)
Roberto Di Pietro (16864155)
author_role author
dc.creator.none.fl_str_mv Omar Adel Ibrahim (18394779)
Gabriele Oligeri (14151426)
Roberto Di Pietro (16864155)
dc.date.none.fl_str_mv 2023-11-17T15:00:00Z
dc.identifier.none.fl_str_mv 10.1016/j.dib.2023.109782
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/A_dataset_of_barometric_readings_for_enhancing_security_and_privacy_of_IoT/26641819
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Engineering
Electronics, sensors and digital hardware
Information and computing sciences
Cybersecurity and privacy
Contextual security
Context-based pairing
Pressure-based authentication
Zero-interaction
IoT
Proximity-based authentication
dc.title.none.fl_str_mv A dataset of barometric readings for enhancing security and privacy of IoT
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p>The security and privacy of wireless channels is typically enforced by leveraging cryptographic tools. However, there are scenarios where these methods are unfit, such as in resource-constrained environments, i.e., Internet of Things (IoT), or when an extra layer of security is needed. A promising solution involves correlating air pressure (barometric) readings to securely pair IoT devices while requiring zero-interaction. This paper presents an experimental dataset of real-world barometric measurements collected in open areas under different weather conditions. Specifically, our dataset includes readings recorded using the reference hardware platform BMP280. The experiments involve a reference scenario constituted by three Adafruit BMP280 barometric sensors connected to a Raspberry Pi 3 Model B board to collect barometric measurements. The three sensors represent two communicating parties (Alice and Bob) and an adversary (Eve), respectively. The dataset is constituted by three experiments characterized by different relative distances among Alice, Bob, and Eve. We considered 5cm and 2m between Alice and Bob while placing Eve at 2m and 8 meters, respectively. The second configuration, i.e., (Alice-Bob at 2m and Eve at 8m) has been replicated in a different scenario characterized by less air pressure fluctuations. The sampling frequency has been set to 70Hz while the measurements last for 50, 24 and 41 hours, respectively. Researchers can use this dataset in several ways, including: (i) Study the air pressure variation and correlation between devices separated by different distances, (ii) Develop a co-location verification extension for the Diffie-Hellman (DH) key agreement method that utilizes air pressure data streams, (iii) Study possible attacks against proximity-based authentication techniques that depend on pressure correlated variations.</p><h2>Other Information</h2> <p> Published in: Data in Brief<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.dib.2023.109782" target="_blank">https://dx.doi.org/10.1016/j.dib.2023.109782</a></p>
eu_rights_str_mv openAccess
id Manara2_cf7e3010adac022573cf3dbcdeaf680f
identifier_str_mv 10.1016/j.dib.2023.109782
network_acronym_str Manara2
network_name_str Manara2
oai_identifier_str oai:figshare.com:article/26641819
publishDate 2023
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spelling A dataset of barometric readings for enhancing security and privacy of IoTOmar Adel Ibrahim (18394779)Gabriele Oligeri (14151426)Roberto Di Pietro (16864155)EngineeringElectronics, sensors and digital hardwareInformation and computing sciencesCybersecurity and privacyContextual securityContext-based pairingPressure-based authenticationZero-interactionIoTProximity-based authentication<p>The security and privacy of wireless channels is typically enforced by leveraging cryptographic tools. However, there are scenarios where these methods are unfit, such as in resource-constrained environments, i.e., Internet of Things (IoT), or when an extra layer of security is needed. A promising solution involves correlating air pressure (barometric) readings to securely pair IoT devices while requiring zero-interaction. This paper presents an experimental dataset of real-world barometric measurements collected in open areas under different weather conditions. Specifically, our dataset includes readings recorded using the reference hardware platform BMP280. The experiments involve a reference scenario constituted by three Adafruit BMP280 barometric sensors connected to a Raspberry Pi 3 Model B board to collect barometric measurements. The three sensors represent two communicating parties (Alice and Bob) and an adversary (Eve), respectively. The dataset is constituted by three experiments characterized by different relative distances among Alice, Bob, and Eve. We considered 5cm and 2m between Alice and Bob while placing Eve at 2m and 8 meters, respectively. The second configuration, i.e., (Alice-Bob at 2m and Eve at 8m) has been replicated in a different scenario characterized by less air pressure fluctuations. The sampling frequency has been set to 70Hz while the measurements last for 50, 24 and 41 hours, respectively. Researchers can use this dataset in several ways, including: (i) Study the air pressure variation and correlation between devices separated by different distances, (ii) Develop a co-location verification extension for the Diffie-Hellman (DH) key agreement method that utilizes air pressure data streams, (iii) Study possible attacks against proximity-based authentication techniques that depend on pressure correlated variations.</p><h2>Other Information</h2> <p> Published in: Data in Brief<br> License: <a href="http://creativecommons.org/licenses/by/4.0/" target="_blank">http://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1016/j.dib.2023.109782" target="_blank">https://dx.doi.org/10.1016/j.dib.2023.109782</a></p>2023-11-17T15:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1016/j.dib.2023.109782https://figshare.com/articles/journal_contribution/A_dataset_of_barometric_readings_for_enhancing_security_and_privacy_of_IoT/26641819CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/266418192023-11-17T15:00:00Z
spellingShingle A dataset of barometric readings for enhancing security and privacy of IoT
Omar Adel Ibrahim (18394779)
Engineering
Electronics, sensors and digital hardware
Information and computing sciences
Cybersecurity and privacy
Contextual security
Context-based pairing
Pressure-based authentication
Zero-interaction
IoT
Proximity-based authentication
status_str publishedVersion
title A dataset of barometric readings for enhancing security and privacy of IoT
title_full A dataset of barometric readings for enhancing security and privacy of IoT
title_fullStr A dataset of barometric readings for enhancing security and privacy of IoT
title_full_unstemmed A dataset of barometric readings for enhancing security and privacy of IoT
title_short A dataset of barometric readings for enhancing security and privacy of IoT
title_sort A dataset of barometric readings for enhancing security and privacy of IoT
topic Engineering
Electronics, sensors and digital hardware
Information and computing sciences
Cybersecurity and privacy
Contextual security
Context-based pairing
Pressure-based authentication
Zero-interaction
IoT
Proximity-based authentication