RESEARCH OF THE POSSIBILITY OF USING SEPARATE MOBILE DEVICE SENSORS AS A SOURCE OF ENTROPY FOR A RANDOM NUMBER GENERATOR

Abstract

This paper explores the potential of utilizing the accelerometer, gyroscope, and magnetometer sensors embedded in modern mobile devices as novel entropy sources for hardware-based random number generators (RNGs). The study begins by defining the fundamental requirements for effective entropy sources, followed by a detailed comparative analysis of available mobile device sensors. Based on this analysis, specific sensors were selected for further investigation due to their responsiveness, accessibility, and variability in data output. A specialized software-hardware complex was developed, comprising a smartphone for data acquisition and a personal computer for processing and analysis. This system enables the extraction of raw sensor data and supports experimentation with different bit-level manipulations.

The research examines the use of between 1 to 32 least significant bits (LSBs) from each axis (X, Y, Z) of the selected sensors. Various methods for combining these bits—such as simple concatenation, arithmetic summation, and modulo two addition (XOR)—are implemented and analyzed. Experimental evaluations focus on the statistical quality of the generated random numbers, their compliance with standard randomness criteria, and the throughput of generation.

The findings indicate that sensor data from mobile devices can serve as viable entropy sources, significantly enhancing the performance and speed of hardware RNGs. This approach not only leverages readily available consumer technology but also offers a scalable and cost-effective solution for secure and efficient random number generation in various applications, including cryptographic systems, simulations, and secure communications.