Advanced security taxonomy for machine-to-machine (M2M) communications in 5G capillary networks

Abstract Machine-to-machine (M2M) communications, as part of emerging 5th-generation (5G) communications networks, are growing in rollouts and importance due to their ability to deliver data in real time from the field. In these networks, thousands of devices are left unattended for years of operation without the possibility of human intervention. For that reason, the protection of data, infrastructure, and communications is of paramount importance. To facilitate a better understanding of the field, we propose a security taxonomy for allowing an exhaustive and complete analysis related to several security issues that range from the available architectures to implemented protocols. In more detail, we focus on security aspects related to the most-common architectures, the valuable assets, the typical threats, the counteracting services, the protocols carrying out these services, and the algorithms that are typically used in the M2M context. The security analysis presented in every section provides valuable information for the design of reliable embedded communication systems and the identification of necessary future lines of investigation for supporting the development of more secure and efficient M2M communications in 5G capillary networks.