Artificial Intelligence-(AI-) Enabled Internet of Things (IoT) for Secure Big Data Processing in Multihoming Networks

dc.contributor.authorRathee, Geetanjali
dc.contributor.authorKhelifi, Adel
dc.contributor.authorIqbal, Razi
dc.date.accessioned2022-05-11T05:59:36Z
dc.date.accessioned2023-08-19T08:18:13Z
dc.date.available2022-05-11T05:59:36Z
dc.date.available2023-08-19T08:18:13Z
dc.date.issued2021-08
dc.description.abstractThe automated techniques enabled with Artificial Neural Networks (ANN), Internet of Things (IoT), and cloud-based services affect the real-time analysis and processing of information in a variety of applications. In addition, multihoming is a type of network that combines various types of networks into a single environment while managing a huge amount of data. Nowadays, the big data processing and monitoring in multihoming networks provide less attention while reducing the security risk and efficiency during processing or monitoring the information. The use of AI-based systems in multihoming big data with IoT- and AI-integrated systems may benefit in various aspects. Although multihoming security issues and their analysis have been well studied by various scientists and researchers; however, not much attention is paid towards big data security processing in multihoming especially using automated techniques and systems. The aim of this paper is to propose an IoT-based artificial network to process and compute big data processing by ensuring a secure communication multihoming network using the Bayesian Rule (BR) and Levenberg-Marquardt (LM) algorithms. Further, the efficiency and effect on multihoming information processing using an AI-assisted mechanism are experimented over various parameters such as classification accuracy, classification time, specificity, sensitivity, ROC, and -measure.en_US
dc.identifier.citationRathee, G., Khelifi, A., & Iqbal, R. (2021). Artificial Intelligence-(AI-) Enabled Internet of Things (IoT) for Secure Big Data Processing in Multihoming Networks. Wireless Communications and Mobile Computing, 2021.‏en_US
dc.identifier.doihttps://doi.org/10.1155/2021/5754322
dc.identifier.urihttps://edms.wexl.in/handle/1/3395
dc.language.isoenen_US
dc.publisherWileyen_US
dc.subjectArtificial Neural Networksen_US
dc.subjectInternet of Things (IoT)en_US
dc.subjectLevenberg-Marquardt (LM)en_US
dc.subjectBayesian Ruleen_US
dc.titleArtificial Intelligence-(AI-) Enabled Internet of Things (IoT) for Secure Big Data Processing in Multihoming Networksen_US
dc.title.alternativeJournal articleen_US
dc.typeArticleen_US

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