Detecting Anomalous Network Traffic with Combined Fuzzy-Based Approaches
作者： Hai-Tao He , Xiao-Nan Luo , Bao-Lu Liu
DOI: 10.1007/11538356_45
关键词:
摘要: This paper introduces the combined fuzzy-based approaches to detect anomalous network traffic such as DoS/DDoS or probing attacks, which include Adaptive Neuro-Fuzzy Inference System (ANFIS) and Fuzzy C-Means (FCM) clustering. The basic idea of algorithm is: at first using ANFIS original multi-dimensional (M-D) feature space connections is transformed a compact one-dimensional (1-D) space, secondly FCM clustering used classify 1-D into normal.PCA also for dimensional reduction during extraction. combines advantages high accuracy in supervised learning technique speed unsupervised technique. A publicly available DRAPA/KDD99 dataset demonstrate results show their detecting anomalies connections.
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