A technical review of wireless security for the internet of things: Software defined radio perspective
The increase of cyberattacks by using the Internet of Things devices has exposed multiple vulnerabilities not only on devices but also on IoT infrastructures. Now, small devices can affect different networks and their services. This paper presents a review of the vulnerabilities on wireless technolo...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-07-01
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| Series: | Journal of King Saud University: Computer and Information Sciences |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1319157821000896 |
| _version_ | 1811329414951075840 |
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| author | José de Jesús Rugeles Uribe Edward Paul Guillen Leonardo S. Cardoso |
| author_facet | José de Jesús Rugeles Uribe Edward Paul Guillen Leonardo S. Cardoso |
| author_sort | José de Jesús Rugeles Uribe |
| collection | DOAJ |
| description | The increase of cyberattacks by using the Internet of Things devices has exposed multiple vulnerabilities not only on devices but also on IoT infrastructures. Now, small devices can affect different networks and their services. This paper presents a review of the vulnerabilities on wireless technologies that gives connectivity to IoT, and the experiences using Software Defined Radio SDR for implementing wireless attacks to IoT technologies are assessed. A systematic literature review was conducted. The types of vulnerabilities and attacks that can affect the wireless technologies that stand the IoT ecosystem and SDR platforms were compared, and recent methods to overcome these attacks were identified. On the IoT reference model, the perception layer was identified as the most vulnerable. Most attacks at this level occur due to hardware limitations, physical device exposure, and heterogeneity of technologies. Future cybersecurity systems based on SDR technologies have notable advantages due to their flexibility and adaptability to new communication technologies and their potential to develop advanced tools. However, the IoT’s cybersecurity challenges are so complex that merging SDR hardware with cognitive and intelligent techniques is highly advisable. Some of these techniques could include deep learning to adapt mitigation systems to rapid technological changes. |
| first_indexed | 2024-04-13T15:43:25Z |
| format | Article |
| id | doaj.art-cd5265c899224bbb8b9b2219befca77d |
| institution | Directory Open Access Journal |
| issn | 1319-1578 |
| language | English |
| last_indexed | 2024-04-13T15:43:25Z |
| publishDate | 2022-07-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of King Saud University: Computer and Information Sciences |
| spelling | doaj.art-cd5265c899224bbb8b9b2219befca77d2022-12-22T02:41:03ZengElsevierJournal of King Saud University: Computer and Information Sciences1319-15782022-07-0134741224134A technical review of wireless security for the internet of things: Software defined radio perspectiveJosé de Jesús Rugeles Uribe0Edward Paul Guillen1Leonardo S. Cardoso2Research team in Security and Communications Systems (GISSIC), Cajicá, Colombia; Corresponding author.Research team in Security and Communications Systems (GISSIC), Cajicá, ColombiaCITI, Villeurbanne, FranceThe increase of cyberattacks by using the Internet of Things devices has exposed multiple vulnerabilities not only on devices but also on IoT infrastructures. Now, small devices can affect different networks and their services. This paper presents a review of the vulnerabilities on wireless technologies that gives connectivity to IoT, and the experiences using Software Defined Radio SDR for implementing wireless attacks to IoT technologies are assessed. A systematic literature review was conducted. The types of vulnerabilities and attacks that can affect the wireless technologies that stand the IoT ecosystem and SDR platforms were compared, and recent methods to overcome these attacks were identified. On the IoT reference model, the perception layer was identified as the most vulnerable. Most attacks at this level occur due to hardware limitations, physical device exposure, and heterogeneity of technologies. Future cybersecurity systems based on SDR technologies have notable advantages due to their flexibility and adaptability to new communication technologies and their potential to develop advanced tools. However, the IoT’s cybersecurity challenges are so complex that merging SDR hardware with cognitive and intelligent techniques is highly advisable. Some of these techniques could include deep learning to adapt mitigation systems to rapid technological changes.http://www.sciencedirect.com/science/article/pii/S1319157821000896Internet of thingsSoftware Defined Radio (SDR)CybersecurityRadio communicationCyberattackVulnerabilities |
| spellingShingle | José de Jesús Rugeles Uribe Edward Paul Guillen Leonardo S. Cardoso A technical review of wireless security for the internet of things: Software defined radio perspective Journal of King Saud University: Computer and Information Sciences Internet of things Software Defined Radio (SDR) Cybersecurity Radio communication Cyberattack Vulnerabilities |
| title | A technical review of wireless security for the internet of things: Software defined radio perspective |
| title_full | A technical review of wireless security for the internet of things: Software defined radio perspective |
| title_fullStr | A technical review of wireless security for the internet of things: Software defined radio perspective |
| title_full_unstemmed | A technical review of wireless security for the internet of things: Software defined radio perspective |
| title_short | A technical review of wireless security for the internet of things: Software defined radio perspective |
| title_sort | technical review of wireless security for the internet of things software defined radio perspective |
| topic | Internet of things Software Defined Radio (SDR) Cybersecurity Radio communication Cyberattack Vulnerabilities |
| url | http://www.sciencedirect.com/science/article/pii/S1319157821000896 |
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