A fully CMOS true random number generator based on hidden attractor hyperchaotic system

Abstract

Low-power devices used in Internet-of-things networks have been short of security due to the high power consumption of random number generators. This paper presents a low-power hyperchaos-based true random number generator, which is highly recommended for secure communications. The proposed system, which is based on a four-dimensional chaotic system with hidden attractors and oscillators, exhibits rich dynamics. Numerical analysis is provided to verify the dynamic characteristics of the proposed system. A fully customized circuit is deployed using 130 nm CMOS technology to enable integration into low-power devices. Four output signals are used to seed a SHIFT-XOR-based chaotic data post-processing to generate random bit output. The chip prototype was simulated and tested at 100 MHz sampling frequency. The hyperchaotic circuit consumes a maximum of 980 $$\upmu $$ μ W in generating chaotic signals while dissipates a static current of 623 $$\upmu $$ μ A. Moreover, the proposed system provides ready-to-use binary random bit sequences which have passed the well-known statistical randomness test suite NIST SP800-22. The proposed novel system design and its circuit implementation provide a best energy efficiency of 4.37 pJ/b at a maximum sampling frequency of 100 MHz.

Chaos in the Real World: Recent Applications to Communications, Computing, Distributed Sensing, Robotic Motion, Bio-Impedance Modelling and Encryption Systems

“…Herein two main topics are discussed. One issue regards the hardware implementations of encryption systems [18][19][20][21][22][23][24][25][26], whereas the other is related to the capability of chaotic systems to generate random numbers [27][28][29][30][31][32][33][34][35].…”

“…Since randomness and unpredictability are required by encryption, it is clear that chaos has good features in this regard, by virtue of the sensitive dependence on initial conditions, periodicity and reproduction. Some interesting manuscripts have been recently published on the topic [27][28][29][30][31][32][33][34][35]. For example, in [27] the dynamics of some discrete-time chaotic systems in the digital (i.e., finite-precision) domain is studied.…”

“…In [28], it is pointed out that low-power devices used in Internet-of-things networks currently lack security owing to the high power consumption of random number generators. Consequently, the authors of reference [28] present a low-power true random number generator that exploits a four-dimensional hyperchaotic system characterized by hidden attractors. A customized circuit is realized using 130 nm CMOS technology, with the aim to integrate it into low-power devices.…”

“…A customized circuit is realized using 130 nm CMOS technology, with the aim to integrate it into low-power devices. Moreover, chaotic data post-processing via SHIFT-XOR is exploited to produce random bit outputs [28]. The consumption of the hyperchaotic circuit reaches the maximum value of 980µW to generate the chaotic signals, whereas the dissipation of the static current is about 623µA.…”

“…In Section 5 it is shown how chaos can give significant insights to the quality assessments of fruits and vegetables [17]. Section 6 presents some applications of chaos to the hardware implementation of encryption systems [18][19][20][21][22][23][24][25][26] and to random number generation [27][28][29][30][31][32][33][34][35], including the use of chaos for secure transfer of medical images. Finally, Section 7 illustrates how chaos-based logic gates can be used for computing [36], whereas Section 8 highlights how chaos can be exploited in neuromorphic applications [37,38].…”