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Hybrid-AI-Based iBeacon Indoor Positioning Cybersecurity: Attacks and Defenses
iBeacon systems have been increasingly established in public areas to assist users in terms of indoor location navigation and positioning. People receive the services through the Bluetooth Low Energy (BLE) installed on their mobile phones. However, the positioning and navigation functions of an iBea...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9960732/ https://www.ncbi.nlm.nih.gov/pubmed/36850754 http://dx.doi.org/10.3390/s23042159 |
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author | Huang, Chi-Jan Chi, Cheng-Jan Hung, Wei-Tzu |
author_facet | Huang, Chi-Jan Chi, Cheng-Jan Hung, Wei-Tzu |
author_sort | Huang, Chi-Jan |
collection | PubMed |
description | iBeacon systems have been increasingly established in public areas to assist users in terms of indoor location navigation and positioning. People receive the services through the Bluetooth Low Energy (BLE) installed on their mobile phones. However, the positioning and navigation functions of an iBeacon system may be compromised when faced with cyberattacks issued by hackers. In other words, its security needs to be further considered and enhanced. This study took the iBeacon system of Taipei Main Station, the major transportation hub with daily traffic of at least three hundred thousand passengers, as an example for exploring its potential attacks and further studying the defense technologies, with the assistance of AI techniques and human participation. Our experiments demonstrate that in the early stage of iBeacon system information security planning, information security technology and a rolling coding encryption should be included, representing the best defense methods at present. In addition, we believe that the adoption of rolling coding is the most cost-effective defense. However, if the security of critical infrastructure is involved, the most secure defense method should be adopted, namely a predictable and encrypted rolling coding method. |
format | Online Article Text |
id | pubmed-9960732 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-99607322023-02-26 Hybrid-AI-Based iBeacon Indoor Positioning Cybersecurity: Attacks and Defenses Huang, Chi-Jan Chi, Cheng-Jan Hung, Wei-Tzu Sensors (Basel) Article iBeacon systems have been increasingly established in public areas to assist users in terms of indoor location navigation and positioning. People receive the services through the Bluetooth Low Energy (BLE) installed on their mobile phones. However, the positioning and navigation functions of an iBeacon system may be compromised when faced with cyberattacks issued by hackers. In other words, its security needs to be further considered and enhanced. This study took the iBeacon system of Taipei Main Station, the major transportation hub with daily traffic of at least three hundred thousand passengers, as an example for exploring its potential attacks and further studying the defense technologies, with the assistance of AI techniques and human participation. Our experiments demonstrate that in the early stage of iBeacon system information security planning, information security technology and a rolling coding encryption should be included, representing the best defense methods at present. In addition, we believe that the adoption of rolling coding is the most cost-effective defense. However, if the security of critical infrastructure is involved, the most secure defense method should be adopted, namely a predictable and encrypted rolling coding method. MDPI 2023-02-14 /pmc/articles/PMC9960732/ /pubmed/36850754 http://dx.doi.org/10.3390/s23042159 Text en © 2023 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 Huang, Chi-Jan Chi, Cheng-Jan Hung, Wei-Tzu Hybrid-AI-Based iBeacon Indoor Positioning Cybersecurity: Attacks and Defenses |
title | Hybrid-AI-Based iBeacon Indoor Positioning Cybersecurity: Attacks and Defenses |
title_full | Hybrid-AI-Based iBeacon Indoor Positioning Cybersecurity: Attacks and Defenses |
title_fullStr | Hybrid-AI-Based iBeacon Indoor Positioning Cybersecurity: Attacks and Defenses |
title_full_unstemmed | Hybrid-AI-Based iBeacon Indoor Positioning Cybersecurity: Attacks and Defenses |
title_short | Hybrid-AI-Based iBeacon Indoor Positioning Cybersecurity: Attacks and Defenses |
title_sort | hybrid-ai-based ibeacon indoor positioning cybersecurity: attacks and defenses |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9960732/ https://www.ncbi.nlm.nih.gov/pubmed/36850754 http://dx.doi.org/10.3390/s23042159 |
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