A Secure Intrusion Detection Platform Using Blockchain and Radial Basis Function Neural Networks for Internet of Drones

dc.authoridHeidari, Arash/0000-0003-4279-8551
dc.authoridJafari Navimipour, Nima/0000-0002-5514-5536
dc.authoridHeidary, Amir/0000-0002-5265-4634
dc.authoridLekic, Aleksandra/0000-0003-2727-0767
dc.authoridPopov, Marjan/0000-0001-7292-5334
dc.authorwosidHeidari, Arash/AAK-9761-2021
dc.authorwosidJafari Navimipour, Nima/AAF-5662-2021
dc.authorwosidHeidary, Amir/T-2480-2017
dc.contributor.authorJafari Navimipour, Nima
dc.contributor.authorNavimipour, Nima Jafari
dc.contributor.authorUnal, Mehmet
dc.date.accessioned2023-10-19T15:11:54Z
dc.date.available2023-10-19T15:11:54Z
dc.date.issued2023
dc.department-temp[Heidari, Arash] Islamic Azad Univ, Dept Comp Engn, Tabriz Branch, Tabriz 5157944533, Iran; [Navimipour, Nima Jafari] Kadir Has Univ, Fac Engn & Nat Sci, Dept Comp Engn, TR-34083 Istanbul, Turkiye; [Unal, Mehmet] Nisantasi Univ, Dept Comp Engn, TR-34485 Istanbul, Turkiyeen_US
dc.description.abstractThe Internet of Drones (IoD) is built on the Internet of Things (IoT) by replacing Things with Drones while retaining incomparable features. Because of its vital applications, IoD technologies have attracted much attention in recent years. Nevertheless, gaining the necessary degree of public acceptability of IoD without demonstrating safety and security for human life is exceedingly difficult. In addition, intrusion detection systems (IDSs) in IoD confront several obstacles because of the dynamic network architecture, particularly in balancing detection accuracy and efficiency. To increase the performance of the IoD network, we proposed a blockchain-based radial basis function neural networks (RBFNNs) model in this article. The proposed method can improve data integrity and storage for smart decision-making across different IoDs. We discussed the usage of blockchain to create decentralized predictive analytics and a model for effectively applying and sharing deep learning (DL) methods in a decentralized fashion. We also assessed the model using a variety of data sets to demonstrate the viability and efficacy of implementing the blockchain-based DL technique in IoD contexts. The findings showed that the suggested model is an excellent option for developing classifiers while adhering to the constraints placed by network intrusion detection. Furthermore, the proposed model can outperform the cutting-edge methods in terms of specificity, F1, recall, precision, and accuracy.en_US
dc.identifier.citation36
dc.identifier.doi10.1109/JIOT.2023.3237661en_US
dc.identifier.endpage8454en_US
dc.identifier.issn2327-4662
dc.identifier.issue10en_US
dc.identifier.scopus2-s2.0-85147274038en_US
dc.identifier.scopusqualityQ1
dc.identifier.startpage8445en_US
dc.identifier.urihttps://doi.org/10.1109/JIOT.2023.3237661
dc.identifier.urihttps://hdl.handle.net/20.500.12469/5269
dc.identifier.volume10en_US
dc.identifier.wosWOS:000982455700010en_US
dc.identifier.wosqualityQ1
dc.khas20231019-WoSen_US
dc.language.isoenen_US
dc.publisherIEEE-Inst Electrical Electronics Engineers Incen_US
dc.relation.ispartofIeee Internet of Things Journalen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectDronesen_US
dc.subjectBlockchainsen_US
dc.subjectSecurityen_US
dc.subject5G mobile communicationen_US
dc.subjectInternet of Thingsen_US
dc.subjectComputer architectureen_US
dc.subjectAdaptation modelsen_US
dc.subjectBlockchainen_US
dc.subjectUnmanned Aerial VehicleEn_Us
dc.subjectintrusion detection system (IDS)en_US
dc.subjectInternet of Drones (IoD)en_US
dc.subjectUnmanned Aerial Vehicle
dc.subjectsecurityen_US
dc.titleA Secure Intrusion Detection Platform Using Blockchain and Radial Basis Function Neural Networks for Internet of Dronesen_US
dc.typeArticleen_US
dspace.entity.typePublication
relation.isAuthorOfPublication0fb3c7a0-c005-4e5f-a9ae-bb163df2df8e
relation.isAuthorOfPublication.latestForDiscovery0fb3c7a0-c005-4e5f-a9ae-bb163df2df8e

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