Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review

<p dir="ltr">Energy efficiency and safety are two essential factors that play a significant role in operating a wireless sensor network. However, it is claimed that these two factors are naturally conflicting. The level of electrical consumption required by a security system is direc...

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التفاصيل البيبلوغرافية
المؤلف الرئيسي: Yazeed Yasin Ghadi (16667109) (author)
مؤلفون آخرون: Tehseen Mazhar (19332663) (author), Tamara Al Shloul (21633554) (author), Tariq Shahzad (21632645) (author), Umair Ahmad Salaria (21633557) (author), Arfan Ahmed (17541309) (author), Habib Hamam (21633560) (author)
منشور في: 2024
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author Yazeed Yasin Ghadi (16667109)
author2 Tehseen Mazhar (19332663)
Tamara Al Shloul (21633554)
Tariq Shahzad (21632645)
Umair Ahmad Salaria (21633557)
Arfan Ahmed (17541309)
Habib Hamam (21633560)
author2_role author
author
author
author
author
author
author_facet Yazeed Yasin Ghadi (16667109)
Tehseen Mazhar (19332663)
Tamara Al Shloul (21633554)
Tariq Shahzad (21632645)
Umair Ahmad Salaria (21633557)
Arfan Ahmed (17541309)
Habib Hamam (21633560)
author_role author
dc.creator.none.fl_str_mv Yazeed Yasin Ghadi (16667109)
Tehseen Mazhar (19332663)
Tamara Al Shloul (21633554)
Tariq Shahzad (21632645)
Umair Ahmad Salaria (21633557)
Arfan Ahmed (17541309)
Habib Hamam (21633560)
dc.date.none.fl_str_mv 2024-01-01T00:00:00Z
dc.identifier.none.fl_str_mv 10.1109/access.2024.3355312
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Machine_Learning_Solutions_for_the_Security_of_Wireless_Sensor_Networks_A_Review/29446106
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Information and computing sciences
Artificial intelligence
Computer vision and multimedia computation
Machine learning
Wireless sensor networks
machine learning
WSNs security
LoWPAN
IoT
Security
Sensors
Machine learning
Artificial intelligence
Safety
Training
Internet of Things
Low-power electronics
Personal area networks
dc.title.none.fl_str_mv Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p dir="ltr">Energy efficiency and safety are two essential factors that play a significant role in operating a wireless sensor network. However, it is claimed that these two factors are naturally conflicting. The level of electrical consumption required by a security system is directly proportional to its degree of complexity. Wireless sensor networks require additional security measures above the capabilities of conventional network security protocols, such as encryption and key management. The potential application of machine learning techniques to address network security concerns is frequently discussed. These devices will have complete artificial intelligence capabilities, enabling them to understand their environment and respond. During the training phase, machine-learning systems may face challenges due to the large amount of data required and the complex nature of the training procedure. The main objective of the article is to know about different machine learning algorithms that are used to solve the security issues of wireless sensor networks. This study also focuses on the use of wireless sensor networks in different fields. Furthermore, this study also focuses on different Machine learning algorithms that are used to secure wireless sensor networks. Moreover, this study also addresses issues of adapting machine learning algorithms to accommodate the sensors’ functionalities in the network configuration. Furthermore, this article also focuses on open issues in this field that must be solved.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2024.3355312" target="_blank">https://dx.doi.org/10.1109/access.2024.3355312</a></p>
eu_rights_str_mv openAccess
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identifier_str_mv 10.1109/access.2024.3355312
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oai_identifier_str oai:figshare.com:article/29446106
publishDate 2024
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spelling Machine Learning Solutions for the Security of Wireless Sensor Networks: A ReviewYazeed Yasin Ghadi (16667109)Tehseen Mazhar (19332663)Tamara Al Shloul (21633554)Tariq Shahzad (21632645)Umair Ahmad Salaria (21633557)Arfan Ahmed (17541309)Habib Hamam (21633560)Information and computing sciencesArtificial intelligenceComputer vision and multimedia computationMachine learningWireless sensor networksmachine learningWSNs securityLoWPANIoTSecuritySensorsMachine learningArtificial intelligenceSafetyTrainingInternet of ThingsLow-power electronicsPersonal area networks<p dir="ltr">Energy efficiency and safety are two essential factors that play a significant role in operating a wireless sensor network. However, it is claimed that these two factors are naturally conflicting. The level of electrical consumption required by a security system is directly proportional to its degree of complexity. Wireless sensor networks require additional security measures above the capabilities of conventional network security protocols, such as encryption and key management. The potential application of machine learning techniques to address network security concerns is frequently discussed. These devices will have complete artificial intelligence capabilities, enabling them to understand their environment and respond. During the training phase, machine-learning systems may face challenges due to the large amount of data required and the complex nature of the training procedure. The main objective of the article is to know about different machine learning algorithms that are used to solve the security issues of wireless sensor networks. This study also focuses on the use of wireless sensor networks in different fields. Furthermore, this study also focuses on different Machine learning algorithms that are used to secure wireless sensor networks. Moreover, this study also addresses issues of adapting machine learning algorithms to accommodate the sensors’ functionalities in the network configuration. Furthermore, this article also focuses on open issues in this field that must be solved.</p><h2>Other Information</h2><p dir="ltr">Published in: IEEE Access<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" target="_blank">https://creativecommons.org/licenses/by/4.0/</a><br>See article on publisher's website: <a href="https://dx.doi.org/10.1109/access.2024.3355312" target="_blank">https://dx.doi.org/10.1109/access.2024.3355312</a></p>2024-01-01T00:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1109/access.2024.3355312https://figshare.com/articles/journal_contribution/Machine_Learning_Solutions_for_the_Security_of_Wireless_Sensor_Networks_A_Review/29446106CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/294461062024-01-01T00:00:00Z
spellingShingle Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review
Yazeed Yasin Ghadi (16667109)
Information and computing sciences
Artificial intelligence
Computer vision and multimedia computation
Machine learning
Wireless sensor networks
machine learning
WSNs security
LoWPAN
IoT
Security
Sensors
Machine learning
Artificial intelligence
Safety
Training
Internet of Things
Low-power electronics
Personal area networks
status_str publishedVersion
title Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review
title_full Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review
title_fullStr Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review
title_full_unstemmed Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review
title_short Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review
title_sort Machine Learning Solutions for the Security of Wireless Sensor Networks: A Review
topic Information and computing sciences
Artificial intelligence
Computer vision and multimedia computation
Machine learning
Wireless sensor networks
machine learning
WSNs security
LoWPAN
IoT
Security
Sensors
Machine learning
Artificial intelligence
Safety
Training
Internet of Things
Low-power electronics
Personal area networks