A Malicious Bot Traffic Detection Method in IoT Network Using Machine Learning Techniques

In the context of growing Internet of Things (IoT) technology, this project utilizes the Bot-IoT dataset for detecting malicious traffic. A feature selection technique is proposed to improve the performance of machine learning algorithms for detecting attacks in IoT network traffic. The system implements machine learning algorithms such as Support Vector Machine (SVM) and Naive Bayes (NB). The experimental results show that the proposed method is highly efficient, achieving over 98% accuracy on average for each algorithm