A Low Power Circuit Design for Chaos-Key Based Data Encryption

Abstract

Dynamic and non-linear systems have been used to generate random bits in high-security applications for decades. In this perspective, due to their stochastic characteristic, chaotic systems have been emerging as the natural choice for the generation of random bits. This paper presents the design and the implementation of a chaos-based true random number generator and a chaos-key based data encryption scheme for secure communications. The mathematical expression of the dynamic system is presented and analyzed to evaluate the possibility of chaos occurrence. Then, the chaotic system is realized at the circuit level using 130 nm CMOS technology to generate random bit sequences, which are utilized in data encryption. Chaotic signal outputs of the chaos-based random number generator circuit are sampled at a maximum frequency of 50 MHz, enabling a high throughput of random bits. The core of the chaotic circuit consumes 630µW in static mode and a maximum of 660µW in running mode. The chaos-based one-time pad encryption scheme using the chaos-key generator shows the advantages of using this random number generator in secure communications. In this context, the data secrecy is compared to the advanced encryption standard AES128. Moreover, the design is simulated in different working conditions such as voltage supply and temperature variations, where it is shown that the random bit output benefits from a high entropy per bit and passes the standard statistical test suite (NIST) for cryptographic applications. INDEX TERMS Chaos, random key, security, CMOS, true random number generator, one-time pad encryption, image encryption, and NIST.

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

“…The contribution in [5] is interesting since presents guidelines for the CMOS circuit design of basic building blocks (such as current follower, current mirror, and voltage follower) which are used for obtaining particularly simple saturated nonlinear functions (SNLFs). Finally, in [20], some of the authors of this manuscript presented the design of a 3D continuous chaotic system in CMOS technology, and its engineering application in image encryption. The main point in common between the design in [20] and the chaotic system implementation presented in this manuscript is that they both rely on the analog realization of a tanh(•) nonlinear function.…”

“…Finally, in [20], some of the authors of this manuscript presented the design of a 3D continuous chaotic system in CMOS technology, and its engineering application in image encryption. The main point in common between the design in [20] and the chaotic system implementation presented in this manuscript is that they both rely on the analog realization of a tanh(•) nonlinear function. Yet, the work presented here offers several improvements.…”

“…As demonstrated in [12], many researchers have been improving the complexity of chaotic maps, where higher dimensional chaotic maps, such as Logistic 2D map, Chen hyperchaotic map, and Rossler hyperchaotic map, have been used. Conversely, continuous chaotic systems are presented by differential equations X = F(X ) [20]. Nowadays, continuous chaotic systems achieve higher complexity by conveying integer-order systems into the fractional-order domain [34].…”

Continuation-Based Method to Find Periodic Windows in Bifurcation Diagrams With Applications to the Chua’s Circuit With a Cubic Nonlinearity

“…Knowing the widths of periodic windows one may compute the measures of the set of regular parameters (with periodic behavior) and stochastic parameters (with chaotic behavior). Knowing the positions of periodic windows helps in selecting parameters of the system for the proper operation of chaos-based applications, including random number generators [13], chaos-based encryption [14] and secure communication [15], [16]. Finding periodic windows, especially the narrow ones, is a challenging numerical problem [17].…”

Fast True Random Number Generator Based on Chaotic Oscillation in Self-Feedback Weakly Coupled Superlattices

“…The true random number generator (TRNG) is based on the unpredictable physical random phenomenon [6], which can generate unpredictable and unreproducible true random numbers. Representative TRNGs are mainly based on physical entropy sources such as circuit thermal noise [7], [8], oscillators [9], and chaotic circuits [10], [11]. But the rate of these random number generators is mostly at the Mbit/s level, which makes it difficult to meet the demands of modern communication systems for high-speed random numbers generation.…”