A secure data transmission and efficient data balancing approach for 5G‐based IoT data using UUDIS‐ECC and LSRHS‐CNN algorithms

Due to the realization of 5G technology, the Internet of things (IoT) has made remarkable advancements in recent years. However, security along with data balancing issues is proffered owing to IoT data's growth. The universally unique identifier short input pseudo‐random (SiP) hash‐based ellipt...

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Published inIET communications Vol. 16; no. 5; pp. 571 - 583
Main Authors Yadav, Kusum, Jain, Anurag, Alharbi, Yasser, Alferaidi, Ali, Alkwai, Lulwah M., Ahmed, Nada Mohamed Osman Sid, Hamad, Sawsan Ali Saad
Format Journal Article
LanguageEnglish
Published Stevenage John Wiley & Sons, Inc 01.03.2022
Wiley
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Abstract Due to the realization of 5G technology, the Internet of things (IoT) has made remarkable advancements in recent years. However, security along with data balancing issues is proffered owing to IoT data's growth. The universally unique identifier short input pseudo‐random (SiP) hash‐based elliptic curve cryptography (UUDIS‐ECC) centred secure data transfer (DT) and linear scaling Rock Hyraxes swarm‐based convolutional neural network (LSRHS‐CNN) centred 5G IoT data balancing are proposed here to address those issues. Authentication, destination selection, validation, secure DT, and also load balancing are the proposed method's five phases. Initially, during the registration phase, the Length Nano ID (LNanoID) is created in the authentication. The user is permitted to further communicate if the LNanoID is matched with the already saved LNanoID. The destination is selected if the user is authorized. Utilizing the sender and the receiver's public key, the hash code is produced in the validation centre by the SiP hash function after destination selection. After that, by employing the UUDIS‐ECC algorithm, the IoT data is safely transmitted towards the destination. The 5G IoT data is balanced by using the LSRHS‐CNN algorithm during DT. Superior results are attained by the proposed methods analogized to existing research methods.
AbstractList Due to the realization of 5G technology, the Internet of things (IoT) has made remarkable advancements in recent years. However, security along with data balancing issues is proffered owing to IoT data's growth. The universally unique identifier short input pseudo‐random (SiP) hash‐based elliptic curve cryptography (UUDIS‐ECC) centred secure data transfer (DT) and linear scaling Rock Hyraxes swarm‐based convolutional neural network (LSRHS‐CNN) centred 5G IoT data balancing are proposed here to address those issues. Authentication, destination selection, validation, secure DT, and also load balancing are the proposed method's five phases. Initially, during the registration phase, the Length Nano ID (LNanoID) is created in the authentication. The user is permitted to further communicate if the LNanoID is matched with the already saved LNanoID. The destination is selected if the user is authorized. Utilizing the sender and the receiver's public key, the hash code is produced in the validation centre by the SiP hash function after destination selection. After that, by employing the UUDIS‐ECC algorithm, the IoT data is safely transmitted towards the destination. The 5G IoT data is balanced by using the LSRHS‐CNN algorithm during DT. Superior results are attained by the proposed methods analogized to existing research methods.
Abstract Due to the realization of 5G technology, the Internet of things (IoT) has made remarkable advancements in recent years. However, security along with data balancing issues is proffered owing to IoT data's growth. The universally unique identifier short input pseudo‐random (SiP) hash‐based elliptic curve cryptography (UUDIS‐ECC) centred secure data transfer (DT) and linear scaling Rock Hyraxes swarm‐based convolutional neural network (LSRHS‐CNN) centred 5G IoT data balancing are proposed here to address those issues. Authentication, destination selection, validation, secure DT, and also load balancing are the proposed method's five phases. Initially, during the registration phase, the Length Nano ID (LNanoID) is created in the authentication. The user is permitted to further communicate if the LNanoID is matched with the already saved LNanoID. The destination is selected if the user is authorized. Utilizing the sender and the receiver's public key, the hash code is produced in the validation centre by the SiP hash function after destination selection. After that, by employing the UUDIS‐ECC algorithm, the IoT data is safely transmitted towards the destination. The 5G IoT data is balanced by using the LSRHS‐CNN algorithm during DT. Superior results are attained by the proposed methods analogized to existing research methods.
Author Alharbi, Yasser
Jain, Anurag
Yadav, Kusum
Ahmed, Nada Mohamed Osman Sid
Alkwai, Lulwah M.
Alferaidi, Ali
Hamad, Sawsan Ali Saad
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CitedBy_id crossref_primary_10_1177_09287329241291397
crossref_primary_10_1016_j_heliyon_2024_e39306
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  doi: 10.1145/2905055.2905199
– ident: e_1_2_8_30_1
  doi: 10.1109/JAS.2020.1003132
– ident: e_1_2_8_7_1
  doi: 10.33166/AETiC.2020.05.004
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Snippet Due to the realization of 5G technology, the Internet of things (IoT) has made remarkable advancements in recent years. However, security along with data...
Abstract Due to the realization of 5G technology, the Internet of things (IoT) has made remarkable advancements in recent years. However, security along with...
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SubjectTerms Access control
Access to information
Algorithms
Artificial neural networks
Authentication
Automation
Blockchain
Communications systems
Computer networks
Confidentiality
Curves
Data encryption
Data transfer (computers)
Data transmission
Digital signatures
Efficiency
Hash based algorithms
Internet of Things
Multimedia communications
Network security
Privacy
Protocol
Quality of service
Sensors
Spatial data
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Title A secure data transmission and efficient data balancing approach for 5G‐based IoT data using UUDIS‐ECC and LSRHS‐CNN algorithms
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Volume 16
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