**1. Introduction**

Chaotic flows are mathematical models originated from the rules of defining chaotic behaviors [1,2]. In the former decades, the chaos theory has been employed in numerous fields such as digital signature [3], secure cryptography [4], pseudorandom number generation [5], secure communication [6], weak signal detection [7], DC-DC boost converter [8], image encryption [9], neurophysiology [10], secure data transmission [11], etc. For the control and synchronization purposes of chaotic systems, several techniques like active control [12], fuzzy control [13], linear matrix inequality (LMI) [14], sampled-data control [15], impulsive adaptive control [16], intermittent control [17] and sliding mode control (SMC) [18] have been introduced.

Recently, Wei (2011) announced a chaotic system with no equilibrium point [19]. Jafari et al. (2013) discovered a set of 17 elementary quadratic chaos systems with no equilibrium points [20]. A chaos system possessing a stable equilibrium point was recently found in [21,22]. It is observed that Shilnikov method [23,24] is not applicable to check chaos behavior in special dynamical systems with no equilibrium point or with stable equilibrium points. Such dynamical systems can be viewed as systems with hidden chaotic attractors in scientific computing [24–26]. Chaotic systems with hidden attractors can result in unexpected disastrous behavior in mechanical systems and electronic circuits.

It is stimulating that chaotic flows containing infinite number of equilibrium points have achieved much consideration in the past decade. Especially, structures with uncountable equilibrium points are categorized as systems with hidden attractors [27,28]. Hidden attractors do not have basins of attraction related to the unstable equilibria. As stated by the recent investigations, hidden attractors are fundamental in engineering usages, for instance, radio-physical oscillator [29], multilevel DC/DC converter [30], electromechanical systems [31] or relay system with hysteresis [32].

In recent years, some new chaotic flows have been planned via cascade chaos, dimension expansion, and physics modelling [1,33]. An extensive body of scientists has been devoted on counteracting degradation and performance improvement of existing chaotic flows. As chaos is broadly employed in nonlinear control, synchronization, and other usages, the design problem of the chaotic flows with complex chaotic behaviors is more attractive [34].

In addition, a widespread application of chaotic systems is that of encryption schemes, voice, text or image. In these schemes, RNGs are the most basic constructs. The fact that the numbers used in encryption have a high randomness and a big impact on the quality of the encryption. In the last few years, some encryption schemes, especially for sound messages, based mainly on discrete chaotic maps, have been presented. In 2016, Sadkhan et al. presented a new speech scrambling system using a hybrid use of different chaotic maps [35]. In 2018, Mobayen et al. proposed the implementation of a sound encryption method based on a novel chaotic system with boomerang-shaped equilibrium [36]. On the same year, Raheema et al. presented an efficient Simulink model, speech scrambling based chaotic maps for encryption of data such as voice, video and text, because it possesses high sensitive to initial values and model external parameters [37].

The objective of this article is to investigate a novel chaotic flow with hyperbolic sinusoidal function. The proposed chaotic flow provides a new category of chaotic systems which helps in more perception of chaotic attractors. In this chaotic flow, because of the variations of the parameters, the self-excited attractor and two forms of hidden attractors (no equilibrium point and line of equilibria) are created. Next, the proposed chaotic system with hidden attractors has been used in the design of an RNG algorithm. Finally, this RNG algorithm is used in a sound encryption scheme.

The rest of this work is organized as follows. In the following section, mathematical form of new chaotic structure is given and different scenarios are proposed. Moreover, some discussions for chaotic flow covering dynamic features such as spectrum of the Lyapunov exponents, bifurcation diagrams, and Poincaré map are proposed. In Section 3, the circuit design of presented chaotic flow is provided and PSpice representation of the chaotic attractors is presented. In Section 4, the engineering application containing RNG algorithm design and voice encryption algorithm is described. As a final point, conclusions are provided in Section 5.
