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Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing

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Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing

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dc.contributor.author Rehman, Amjad es_ES
dc.contributor.author Saba, Tanzila es_ES
dc.contributor.author Haseeb, Khalid es_ES
dc.contributor.author Marie-Sainte, Souad Larabi es_ES
dc.contributor.author Lloret, Jaime es_ES
dc.date.accessioned 2022-10-14T18:02:20Z
dc.date.available 2022-10-14T18:02:20Z
dc.date.issued 2021-10 es_ES
dc.identifier.uri http://hdl.handle.net/10251/187827
dc.description.abstract [EN] Internet of Things (IoT) is a developing technology for supporting heterogeneous physical objects into smart things and improving the individuals living using wireless communication systems. Recently, many smart healthcare systems are based on the Internet of Medical Things (IoMT) to collect and analyze the data for infectious diseases, i.e., body fever, flu, COVID-19, shortness of breath, etc. with the least operation cost. However, the most important research challenges in such applications are storing the medical data on a secured cloud and make the disease diagnosis system more energy efficient. Additionally, the rapid explosion of IoMT technology has involved many cyber-criminals and continuous attempts to compromise medical devices with information loss and generating bogus certificates. Thus, the increase in modern technologies for healthcare applications based on IoMT, securing health data, and offering trusted communication against intruders is gaining much research attention. Therefore, this study aims to propose an energy-efficient IoT e-health model using artificial intelligence with homomorphic secret sharing, which aims to increase the maintainability of disease diagnosis systems and support trustworthy communication with the integration of the medical cloud. The proposed model is analyzed and proved its significance against relevant systems. es_ES
dc.description.sponsorship Prince Sultan University, Riyadh Saudi Arabia, (SEED-CCIS-2021{85}) under Artificial Intelligence & Data Analytics Research Lab. CCIS. es_ES
dc.language Inglés es_ES
dc.publisher MDPI AG es_ES
dc.relation.ispartof Energies es_ES
dc.rights Reconocimiento (by) es_ES
dc.subject Health system es_ES
dc.subject Artificial intelligence es_ES
dc.subject Inflectional diseases es_ES
dc.subject Energy efficiency es_ES
dc.subject Homomorphic secrets es_ES
dc.subject.classification INGENIERIA TELEMATICA es_ES
dc.title Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing es_ES
dc.type Artículo es_ES
dc.identifier.doi 10.3390/en14196414 es_ES
dc.relation.projectID info:eu-repo/grantAgreement/AIDA//SEED-CCIS-2021(85)/ es_ES
dc.rights.accessRights Abierto es_ES
dc.contributor.affiliation Universitat Politècnica de València. Departamento de Comunicaciones - Departament de Comunicacions es_ES
dc.description.bibliographicCitation Rehman, A.; Saba, T.; Haseeb, K.; Marie-Sainte, SL.; Lloret, J. (2021). Energy-Efficient IoT e-Health Using Artificial Intelligence Model with Homomorphic Secret Sharing. Energies. 14(19):1-15. https://doi.org/10.3390/en14196414 es_ES
dc.description.accrualMethod S es_ES
dc.relation.publisherversion https://doi.org/10.3390/en14196414 es_ES
dc.description.upvformatpinicio 1 es_ES
dc.description.upvformatpfin 15 es_ES
dc.type.version info:eu-repo/semantics/publishedVersion es_ES
dc.description.volume 14 es_ES
dc.description.issue 19 es_ES
dc.identifier.eissn 1996-1073 es_ES
dc.relation.pasarela S\473233 es_ES
dc.contributor.funder Artificial Intelligence and Data Analytics Lab, Prince Sultan University es_ES


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