Enhancing IoT security: Machine learning and ensemble approaches for intrusion detection

The Internet of Things (IoT) is an advanced network of interconnected devices that collect and share data through connections. It is transforming our lives and working environments, offering opportunities for innovation and efficiency. As the number of interconnected devices increases, so do attacks on user data privacy. This research investigates the importance of Intrusion Detection Systems (IDS) using Ensemble methods and different Machine learning method on CICIDS2017 and also on, IoT Intrusion Detection datasets. This research main aim is to develop IDS systems integrated with computational technologies like machine learning, presenting results for accuracy, precision, recall, and F1-score to improve the efficiency of existing IoT IDS.