IoT and satellite based 5G network security

The integration of the Internet of Things (IoT), 5G and satellite technologies has evolved telecommunication
networks to provide higher quality and more stable service to remote areas. However security concerns with IoT are growing as IoT devices become increasingly attractive targets for cyber attacks due to hugely growing volumes and also poor or nonexistent inbuilt security. In this paper, we propose a IoT and satellite based 5G network security model which is able to harness machine learning to provide more effective detection of cyber
attacks and malware. The solution is divided into two main parts. The creation of the model for intrusion detection using various machine learning (ML) algorithms and the implementation of this ML based model into terrestrial or satellite gateways. This paper will demonstrate that ML algorithms can be used to classify benign or malicious packets in an IoT network to enhance security. Finally, the tested ML algorithms are compared for
effectiveness in terms of accuracy rate, precision, recall, f1-score and false negative rate.