A novel memristive true random number generator design

Abstract

Purpose In this work, a true random number generator is designed by sampling the double-scroll analog continuous-time chaotic circuit signals. Methodology A Chua circuit based on memristance simulator is designed to obtain a non-linear term for a chaotic dynamic system. It is implemented on the board by using commercially available integrated circuits and passive elements. A low precision ADC which is commonly found in the market is used to sample the chaotic signals. The mathematical analysis of the chaotic circuit is verified by experimental results. Originality It is aimed to be one of the pioneering studies (including low precision ADC) in the literature on the implementation of memristive chaotic random number generators. Findings Two new methods are proposed for post-processing and creating random bit array using XOR operator and J-K flip flop. The bit stream obtained by a full-hardware implementation successfully passed the NIST-800-22 test. In this respect, the availability of the memristance simulator circuit, memristive chaotic double-scroll attractor, proposed random bit algorithm and the randomness of the memristive analog continuous-time chaotic true number generator were also verified.

Probabilistic Circuit Implementation Based on P-Bits Using the Intrinsic Random Property of RRAM and P-Bit Multiplexing Strategy

“…Compared with the traditional CMOS random number generator, the random number generator designed with RRAM has the advantages of a small area, low power consumption, and good randomness, which is more attractive [10][11][12][13]. The RRAM stack includes the bottom electrode (BE, TiN), top electrode (TE, TiN), and TaOx layer.…”

Demonstration of Three True Random Number Generator Circuits Using Memristor Created Entropy and Commercial Off-the-Shelf Components

“…Random numbers have a variety of uses in modern computing and information security, ranging from simple decision making in a video game, to encryption of secure documents and keeping banking transactions secure [ 1 , 2 , 3 , 4 , 5 , 6 ]. The security of data and communication channels is especially important today with the increase in connected devices throughout the world.…”

“…That is, if the current state of the PRNG is known, then the future output of the PRNG can be predicted. A primary use of PRNGs is often scientific research and simulations (e.g., Monte Carlo) [ 6 , 9 ].…”

“…A recent approach in TRNG circuits has been to use a memristor device [ 18 , 19 , 20 ] to capture entropy for TRNG circuit designs [ 1 , 2 , 5 , 6 , 15 , 21 , 22 , 23 ]. Many of these designs use the memristors in a circuit that oscillates (e.g., a ring oscillator) or is driven by a pulse generator.…”

“…Last, we build a memristor-based TRNG circuit of our own design and put it through the same tests in order to demonstrate the ease of implementation of memristor-based TRNGs and their accessibility to anyone using commercially available components. While there are other statistical test suites available to test the randomness of RNGs, the NIST STS had the most widespread use in our literature survey, having been used to assess RNGs in [ 1 , 2 , 5 , 6 , 7 , 8 , 14 , 15 , 16 ]. A brief description of each test in the NIST STS can be found in Appendix A .…”