CTWA method related data

This project provides preprocessed datasets for IoT intrusion detection research, prepared to support class incremental learning experiments. The datasets included are:<b>CICIoT2023</b> – A comprehensive IoT network intrusion dataset covering multiple attack types and normal traffic.<b>BotNetIoT</b> – A widely-used IoT botnet dataset that contains various types of cyberattacks and benign network activities.The data has been preprocessed to facilitate the training and evaluation of machine learning models, including feature normalization, redundancy removal, and format standardization. These datasets can be used to develop, benchmark, and validate intrusion detection models, especially in incremental learning settings where new attack classes are introduced over time.<b>Usage:</b>Training and testing of IoT intrusion detection modelsResearch on class incremental learning and continual learningEvaluation of model performance in distinguishing known and unknown attack types<b>File Contents:</b><code>CICIoT2023_preprocessed.csv</code> – Preprocessed CICIoT2023 dataset<code>BotNetIoT_preprocessed.csv</code> – Preprocessed <code>BotNetIoT</code> dataset<b>Potential Applications:</b>Cybersecurity research in IoT environmentsDevelopment of intelligent intrusion detection systemsBenchmarking novel machine learning methods in class incremental learning