Classification of Random Number Generator Applications in IoT: A Comprehensive Taxonomy

Abstract

Randomness is an important issue for Internet of Things (IoT). The need to generate suitable random numbers for IoT devices with resource and size limitations has emerged due to the cryptographic protocols. Although random number generation approaches have been proposed considering IoT device constraints, commonly used software and hardware-based solutions have not been discussed in detail. The main contribution of this paper is the detailed examination of the problems encountered in random number generation in the IoT ecosystem and the proposed solution approaches. In this context, a classification has been proposed for hardware containing random number generator (RNG), which has different usage areas in IoT environments. Based on the presented classification, the characteristics of the devices in terms of resource constraints are examined. This classification serves as a guide for selecting suitable hardware in applications with or without random number needs. Also, basic RNGs and test suites are discussed. Some challenges are summarized by explaining the random numbers usage in the IoT environment. In addition, proposed random number generation scenarios for IoT devices are determined. Success rate analysis is carried out based on these techniques in terms of randomness tests. Software and hardware-based solution methods are detailed to meet the need for random numbers in real-world IoT applications. RNG algorithms actively used in IoT applications, basic working principles, usage areas, and hardware features are summarized. Finally, the problem that arises in generating random numbers in system -on-chip (SoC) systems, one of the proposed classification components, are summarized, and some precautions that can be taken are expressed.