Using Deep Learning Technique to Protect Internet Network from Intrusion in IoT Environment

IoT is growing more common with each passing day, and it is making things smarter by allowing them to share data via the internet. IoT is quickly making the world intelligent by linking the real and digital worlds, with more than 20 billion items expected to be linked by 2024. IoT aims to make our lives easier, but there are many vulnerabilities and attacks within the IoT environment. Many studies provide intrusion detection systems in an IoT environment based on machine learning and deep learning algorithms. The accuracy and efficiency of the solutions provided vary. In this paper, an RNN deep learning algorithm is proposed to introduce a model for intrusion detection within the IoT environment. The NSL-KDD dataset is used to train and test the proposed model. The introduced solution achieved a good accuracy of 87%. In future work, we plan to use optimization algorithms to improve the detection accuracy of our model.