Characterization of AES Implementations on Microprocessor-based IoT Devices

Abstract

The increased proliferation of IoT devices and the emergence of 5G networks have necessitated increased security of data storage and communication in such connected devices. Thus, cryptography is used in IoT environments to provide secrecy and integrity to the data as well as both authentication and anonymity to the communications across the IoT network. However, IoT devices are resource-constrained devices; have limited memory, network bandwidth, power, and compute units. Since most of the existing cryptographic algorithms were designed to run on resource powerful devices (e.g., desktops or servers), many of these algorithms may not fit into resource-constrained devices. Therefore, in this work, we present a practical performance analysis of different implementations of the Advanced Encryption Standard (AES), which is the most widely used symmetric-key cryptosystem in the IoT environment. Specifically, we explore execution times, energy consumption, and memory usage of the different AES implementations across 4 different public libraries. Furthermore, our analysis is done using various modes, key sizes, plaintext sizes, and microprocessor-based IoT devices. Our results show that for the same combination of inputs and a given algorithm, different crypto library implementations give results with widely varying relative differences. As per the obtained results, the PyCryptodome library seems to be the most suitable one in terms of both execution time and energy on a resource-constrained IoT device and has the most efficient memory usage.