Performance Evaluation of Sequential Minimal Optimization and K* Algorithms for Predicting Burst Header Packet Flooding Attacks on Optical Burst Switching Networks

dc.contributor.authorEfeoğlu, Ebru
dc.contributor.authorTuna, Gürkan
dc.date.accessioned2024-06-12T10:04:09Z
dc.date.available2024-06-12T10:04:09Z
dc.date.issued2021
dc.departmentTrakya Üniversitesien_US
dc.description.abstractOptical burst switching networks are vulnerable to various threats including Burst Header Packet Flooding attack, Circulating Burst Header attack, Address Spoofing, and Replay attack. Therefore, detecting such threats play a key role in taking appropriate security measures. One of the major challenges in identifying the risks of Burst Header Packet flooding attacks is the lack or insufficiency of reliable historical data. In this paper, firstly, Burst Header Packet flooding attacks are classified into four categories, Misbehaving-Block, Behaving-No Block, Misbehaving-No Block and Misbehaving-Wait, using Naive Bayes and K-Nearest Neighbor algorithms. Using performance metrics obtained both after testing on the same set and after applying 10-fold cross validation, the performance of Naive Bayes and K-Nearest Neighbor algorithms is compared based on commonly used performance metrics. As the results show, compared to Naive Bayes, K-Nearest Neighbor algorithm is more suitable for predicting Burst Header Packet Flooding attacks.en_US
dc.identifier.doi10.17694/bajece.892150
dc.identifier.endpage347en_US
dc.identifier.issn2147-284X
dc.identifier.issue4en_US
dc.identifier.startpage342en_US
dc.identifier.trdizinid468155en_US]
dc.identifier.urihttps://doi.org/10.17694/bajece.892150
dc.identifier.urihttps://search.trdizin.gov.tr/yayin/detay/468155
dc.identifier.urihttps://hdl.handle.net/20.500.14551/12659
dc.identifier.volume9en_US
dc.indekslendigikaynakTR-Dizinen_US
dc.language.isoenen_US
dc.relation.ispartofBalkan Journal of Electrical and Computer Engineeringen_US
dc.relation.publicationcategoryMakale - Ulusal Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.titlePerformance Evaluation of Sequential Minimal Optimization and K* Algorithms for Predicting Burst Header Packet Flooding Attacks on Optical Burst Switching Networksen_US
dc.typeArticleen_US

Dosyalar