A Secure Intrusion Detection Platform Using Blockchain and Radial Basis Function Neural Networks for Internet of Drones
dc.authorid | Heidari, Arash/0000-0003-4279-8551 | |
dc.authorid | Jafari Navimipour, Nima/0000-0002-5514-5536 | |
dc.authorid | Heidary, Amir/0000-0002-5265-4634 | |
dc.authorid | Lekic, Aleksandra/0000-0003-2727-0767 | |
dc.authorid | Popov, Marjan/0000-0001-7292-5334 | |
dc.authorwosid | Heidari, Arash/AAK-9761-2021 | |
dc.authorwosid | Jafari Navimipour, Nima/AAF-5662-2021 | |
dc.authorwosid | Heidary, Amir/T-2480-2017 | |
dc.contributor.author | Jafari Navimipour, Nima | |
dc.contributor.author | Navimipour, Nima Jafari | |
dc.contributor.author | Unal, Mehmet | |
dc.date.accessioned | 2023-10-19T15:11:54Z | |
dc.date.available | 2023-10-19T15:11:54Z | |
dc.date.issued | 2023 | |
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, Turkiye | en_US |
dc.description.abstract | The 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.citation | 36 | |
dc.identifier.doi | 10.1109/JIOT.2023.3237661 | en_US |
dc.identifier.endpage | 8454 | en_US |
dc.identifier.issn | 2327-4662 | |
dc.identifier.issue | 10 | en_US |
dc.identifier.scopus | 2-s2.0-85147274038 | en_US |
dc.identifier.scopusquality | Q1 | |
dc.identifier.startpage | 8445 | en_US |
dc.identifier.uri | https://doi.org/10.1109/JIOT.2023.3237661 | |
dc.identifier.uri | https://hdl.handle.net/20.500.12469/5269 | |
dc.identifier.volume | 10 | en_US |
dc.identifier.wos | WOS:000982455700010 | en_US |
dc.identifier.wosquality | Q1 | |
dc.khas | 20231019-WoS | en_US |
dc.language.iso | en | en_US |
dc.publisher | IEEE-Inst Electrical Electronics Engineers Inc | en_US |
dc.relation.ispartof | Ieee Internet of Things Journal | en_US |
dc.relation.publicationcategory | Makale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanı | en_US |
dc.rights | info:eu-repo/semantics/closedAccess | en_US |
dc.subject | Drones | en_US |
dc.subject | Blockchains | en_US |
dc.subject | Security | en_US |
dc.subject | 5G mobile communication | en_US |
dc.subject | Internet of Things | en_US |
dc.subject | Computer architecture | en_US |
dc.subject | Adaptation models | en_US |
dc.subject | Blockchain | en_US |
dc.subject | Unmanned Aerial Vehicle | En_Us |
dc.subject | intrusion detection system (IDS) | en_US |
dc.subject | Internet of Drones (IoD) | en_US |
dc.subject | Unmanned Aerial Vehicle | |
dc.subject | security | en_US |
dc.title | A Secure Intrusion Detection Platform Using Blockchain and Radial Basis Function Neural Networks for Internet of Drones | en_US |
dc.type | Article | en_US |
dspace.entity.type | Publication | |
relation.isAuthorOfPublication | 0fb3c7a0-c005-4e5f-a9ae-bb163df2df8e | |
relation.isAuthorOfPublication.latestForDiscovery | 0fb3c7a0-c005-4e5f-a9ae-bb163df2df8e |
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