Ddos Attack Detection in Ciciot2023 Dataset Using Two Dimensional Convolutional Neural Network

Abstract

The way devices interact and communicate has been completely transformed by the Internet of Things (IoT), which has resulted in an exponential rise in data output. However, this surge in data also brings difficulties in regard to privacy and classification, particularly in identifying malicious activities within IoT networks. The CICIoT 2023 dataset provides a comprehensive framework for evaluating deep learning models in both multi-class and binary classification tasks. This study employs a 2D Convolutional Neural Network (CNN) to classify IoT traffic, leveraging its Capability for collecting spatial hierarchies in the data. The goal of this study is to add to the increasing amount of research on IoT security by demonstrating the efficacy of 2D CNNs in classifying the CICIoT 2023 dataset, while also exploring the broader landscape of deep learning techniques used in this domain.