DDoS Intrusion Detection Model for IoT Networks using Backpropagation Neural Network

In today's digital landscape, Internet of Things (IoT) networking has grown dramatically broad. The major feature IoT network devices is their ability to connect the internet and interact with it through data collecting exchanging. Distributed Denial Service (DDoS) one form cyber-attacks in which hackers penetrate a single connection then multiple machines are operating together attack target. direct connectivity makes DDoS attacks worse more dangerous. businesses adapted networks streamline operations, allowing intrusions at small large scales take place. Therefore, intrusion detection module not optional today’s business environment. To achieve this objective, paper, an intelligent model proposed detect networks. backpropagation neural network-based framework. results analyzed using different performance measures. proves rate 99.46% accuracy 95.76% up-to-date benchmark CICDDoS2019 dataset. Furthermore, been compared most recent schemes competitive achieved.