A Deep CNN-based Framework for Distributed Denial of Services (DDoS) Attack Detection in Internet of Things (IoT)
Brij Bhooshan Gupta, Akshat Gaurav, Varsha Arya, Pankoo Kim · 2023
As the number of connected devices continues to rise, protecting those networks against DDoS attacks is more important than ever. Due to IoT devices' specific features and limited resources, traditional security procedures frequently need to be more successful in detecting and mitigating DDoS assaults in IoT settings. This research offers a new architecture for DDoS attack detection in IoT networks using Deep Convolutional Neural Networks (CNNs). Our methodology fully uses CNNs' innate strengths in detecting DDoS attacks by collecting spatial and temporal patterns in data. We develop a distributed architecture that can install lightweight CNN models to reduce the computational load on low-powered IoT devices. The suggested framework has the potential to significantly improve the safety and reliability of IoT installations, which will encourage the widespread use of this technology.