Securing 5G Network using low power wireless personal area network

Basit Öğe Kaydı
dc.contributor.authorAl-Sarray, Z.A.
dc.contributor.authorMahmood, M.T.
dc.contributor.authorIbrahim, A.A.
dc.date.accessioned2024-09-29T16:20:48Z
dc.date.available2024-09-29T16:20:48Z
dc.date.issued2020
dc.departmentKarabük Üniversitesien_US
dc.description4th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020 -- 22 October 2020 through 24 October 2020 -- Istanbul -- 165025en_US
dc.description.abstractThe purpose of this work was to get acquainted with wireless communication technologies and the information security challenges they create from the viewpoint of 5G and its preceding technologies. 5th Generation (5G) is becoming a global phenomenon and it is currently being implemented in dozens of countries around the globe with it comes new information security challenges. Potential solutions for the challenges are also offered. The outcome of this research is an overview of information security challenges in 5G using Low-power wireless personal area Network (LPWAN) and in the technologies preceding 5G. Possible information security solutions are presented in this work for the new technologies coming with 5G. This work showed that the new technologies coming with 5G, such as the virtualization of hardware and services as well as the utilization of cloud computing, create completely new areas of attack for networks. With this knowledge, Labelled and Freely Available Dataset from Open-Source Repository will be used and it is possible to prevent attacks targeting networks by implementing necessary information security elements. For the training, testing and validation of our dataset which is an IoT and cyber-security based dataset, a well-known MATLAB R2019a software was used for this purpose. The proposed reinforcement learning algorithm for Securing 5G network is designed for mesh topology from the ground up by the model of the network itself using low power personal area networks. We model the network operating in a finite area with a finite number of nodes distributed inside the area randomly in this algorithm. Hence, we defined the service area of the target network by assuming the finiteness of the network in the model. © 2020 IEEE.en_US
dc.identifier.doi10.1109/ISMSIT50672.2020.9255054
dc.identifier.isbn978-172819090-7
dc.identifier.scopus2-s2.0-85097677607en_US
dc.identifier.scopusqualityN/Aen_US
dc.identifier.urihttps://doi.org/10.1109/ISMSIT50672.2020.9255054
dc.identifier.urihttps://hdl.handle.net/20.500.14619/9344
dc.indekslendigikaynakScopusen_US
dc.language.isoenen_US
dc.publisherInstitute of Electrical and Electronics Engineers Inc.en_US
dc.relation.ispartof4th International Symposium on Multidisciplinary Studies and Innovative Technologies, ISMSIT 2020 - Proceedingsen_US
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subject5G networken_US
dc.subjectIOTen_US
dc.subjectLPWANen_US
dc.subjectReinforcement Learning algorithmen_US
dc.subjectsecurityen_US
dc.titleSecuring 5G Network using low power wireless personal area networken_US
dc.typeConference Objecten_US

Dosyalar

Koleksiyon

Scopus İndeksli Yayınlar Koleksiyonu