Comprehensive Performance Evaluation of Association Rule Mining Algorithms for Border Gateway Protocol Anomaly Detection
Küçük Resim Yok
Tarih
2024
Yazarlar
Dergi Başlığı
Dergi ISSN
Cilt Başlığı
Yayıncı
Institute of Electrical and Electronics Engineers Inc.
Erişim Hakkı
info:eu-repo/semantics/closedAccess
Özet
Association rule mining is a data mining technique that concentrates on uncovering noteworthy connections or associations within a vast database of items. The process entails identifying frequently occurring sets of items and deriving association rules from those sets. Border Gateway Protocol (BGP) serves as the prevalent gateway protocol facilitating communication between autonomous systems, enabling the exchange of routing and reachability information. The occurrence of anomalous behavior in protocol attributes can be attributed to diverse factors such as insufficient provisioning, malicious attacks, traffic or equipment problems, and errors made by network operators. Based on the association rule, the dataset is examined and partitioned into sub-frequent pattern datasets. Each pattern dataset selects a single anomalous frequent itemset for comparison to determine the itemset with the highest anomaly value. The commonly used rule-based machine learning algorithms for anomaly detection include Frequent Pattern (FP) growth and Apriori algorithms. This study aims to use unsupervised algorithms based on association rules in select features to detect BGP anomalies. Additionally, the performance of these algorithms will be evaluated in terms of support, confidence, and accuracy values. Furthermore, the anomaly detection results were presented using a tailored and efficient tool and framework, enhancing the clarity and providing a more precise and detailed understanding of the performance. © 2024 IEEE.
Açıklama
4th International Conference on Emerging Smart Technologies and Applications, eSmarTA 2024 -- 6 August 2024 through 7 August 2024 -- Sana'a -- 202077
Anahtar Kelimeler
Apriori Algorithm, Association rule, BGP Anomaly, Dataset, FP Algorithm, Weka
Kaynak
4th International Conference on Emerging Smart Technologies and Applications, eSmarTA 2024
WoS Q Değeri
Scopus Q Değeri
N/A
