Composite and efficient DDoS attack detection framework for B5G networks
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Amaizu, G. C. | - |
dc.contributor.author | Nwakanma, C., I | - |
dc.contributor.author | Bhardwaj, S. | - |
dc.contributor.author | Lee, J. M. | - |
dc.contributor.author | Kim, D. S. | - |
dc.date.accessioned | 2022-05-16T01:41:38Z | - |
dc.date.available | 2022-05-16T01:41:38Z | - |
dc.date.created | 2022-03-28 | - |
dc.date.issued | 2021-04 | - |
dc.identifier.issn | 1389-1286 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/kumoh/handle/2020.sw.kumoh/21080 | - |
dc.description.abstract | Distributed denial-of-service (DDoS) remains an ever-growing problem that has affected and continues to affect a host of web applications, corporate bodies, and governments. With the advent of fifth-generation (5G) network and beyond 5G (B5G) networks, the number and frequency of occurrence of DDoS attacks are predicted to soar as time goes by, hence there is a need for a sophisticated DDoS detection framework to enable the swift transition to 5G and B5G networks without worrying about the security issues and threats. A range of schemes has been deployed to tackle this issue, but along the line, few limitations have been noticed by the research community about these schemes. Owing to these limitations/drawbacks, this paper proposes a composite and efficient DDoS attack detection framework for 5G and B5G. The proposed detection framework consists of a composite multilayer perceptron which was coupled with an efficient feature extraction algorithm and was built not just to detect a DDoS attack, but also, return the type of DDoS attack it encountered. At the end of the simulations and after testing the proposed framework with an industry-recognized dataset, results showed that the framework is capable of detecting DDoS attacks with a high accuracy score of 99.66% and a loss of 0.011. Furthermore, the results of the proposed detection framework were compared with their contemporaries. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | ELSEVIER | - |
dc.title | Composite and efficient DDoS attack detection framework for B5G networks | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Amaizu, G. C. | - |
dc.contributor.affiliatedAuthor | Nwakanma, C., I | - |
dc.contributor.affiliatedAuthor | Bhardwaj, S. | - |
dc.contributor.affiliatedAuthor | Lee, J. M. | - |
dc.contributor.affiliatedAuthor | Kim, D. S. | - |
dc.identifier.doi | 10.1016/j.comnet.2021.107871 | - |
dc.identifier.wosid | 000750845300007 | - |
dc.identifier.bibliographicCitation | COMPUTER NETWORKS, v.188 | - |
dc.relation.isPartOf | COMPUTER NETWORKS | - |
dc.citation.title | COMPUTER NETWORKS | - |
dc.citation.volume | 188 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Hardware & Architecture | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordPlus | INTERNET | - |
dc.subject.keywordPlus | 5G | - |
dc.subject.keywordPlus | ARCHITECTURE | - |
dc.subject.keywordPlus | MITIGATION | - |
dc.subject.keywordPlus | MOBILE | - |
dc.subject.keywordPlus | THINGS | - |
dc.subject.keywordPlus | IOT | - |
dc.subject.keywordAuthor | Network security | - |
dc.subject.keywordAuthor | 5G | - |
dc.subject.keywordAuthor | DDoS | - |
dc.subject.keywordAuthor | Artificial intelligence | - |
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