Flow-Based DDoS Detection Using Deep Neural Network with Radial Basis Function Neural Network
Ting-Chung Leung, Chung‐Nan Lee · 2022 Asia-Pacific Signal and Information Processing Association Annual Summit and Conference (APSIPA ASC) · 2022
This paper presents a Distributed Denial-of-Services (DDoS) attack detection method using Deep Neural Network (DNN) based on flow-based network information. In the proposed method, Radial Basis Function is adopted for feature selection to enhance the accuracy of the DNN. The flow-based dataset CICIDS2017 is used for training and testing the detection accuracy. Experimental results show that the DDoS detection accuracy of the proposed method under the dataset are 99.37%.