BGP Anomali Tespitinde Hibrit Model Yaklaşimi
Küçük Resim Yok
Tarih
2022
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Border Gateway Protocol (BGP) is important for the quality of the connection between autonomous systems and the domains it is connected to. With attacks made at this level, any anomaly in the network will cause connection failures at the border gateways. In this study, a classification model is proposed by using machine learning and deep learning algorithms for the detection of BGP anomalies. The proposed model is developed based on decision trees and random forest and multilayer perceptron algorithms. Indirect BGP anomalies and connection failure anomalies in the model were evaluated with accuracy and F1-score. In the tests performed on the Slammer dataset, it was seen that the best result was obtained with 99,47 accuracy, and 98,85 F1-Score value in the model studied with the Hybrit Model. © 2022 IEEE.
Açıklama
30th Signal Processing and Communications Applications Conference, SIU 2022 -- 15 May 2022 through 18 May 2022 -- Safranbolu -- 182415
Anahtar Kelimeler
Anomaly, BGP, Internet Exchange Point
Kaynak
2022 30th Signal Processing and Communications Applications Conference, SIU 2022
WoS Q Değeri
Scopus Q Değeri
N/A
