Sensors, Vol. 24, Pages 1040: Multi-Stage Learning Framework Using Convolutional Neural Network and Decision Tree-Based Classification for Detection of DDoS Pandemic Attacks in SDN-Based SCADA Systems

This study proposes a multi-stage learning model using a 1-dimensional convolutional neural network (1D-CNN) and decision tree-based classification to detect DDoS attacks in SDN-based SCADA systems effectively. A new dataset containing various attack scenarios on a specific experimental network topology was created to be used in the training and testing phases of this model. According to the experimental results of this study, the proposed model achieved a 97.8% accuracy rate in DDoS-attack detection. The proposed multi-stage learning model shows that high-performance results can be achieved in detecting DDoS attacks against SDN-based SCADA systems.

Source: Sensors - February 5, 2024 Category: Biotechnology Authors: Onur Polat Muammer T ürkoğlu H üseyin Polat Saadin Oyucu H üseyin Üzen Fahri Yard ımcı Ahmet Aks öz Tags: Article Source Type: research