## 1 Introduction  
As we increasingly rely on intelligent and interconnected devices in every aspect of our lives (residences, transports, hospitals, factories,...), how do we protect potentially billions of these connected devices from passive and active attacks that could compromise personal privacy or threaten public safety? We all live today in a cyber world. For that, most of the world's web traffic (digital multimedia content such as images and videos, emails) is encrypted because of security threats. The revised eSTREAM project, September 2008, contains seven stream ciphers that fall into two profiles. Profile 1 contains HC-128, Rabbit, Salsa20/12, and SOSEMANUK stream ciphers, which are best suited for software applications requiring high throughput. Profile 2 contains Grain, MICKEY 2.0, and Trivium stream ciphers, which are particularly suitable for hardware applications with constrained resources and limited power consumption [1, 2]. However, these days, most of these stream ciphers are weak against various attacks and then can't be used to secure exchanged and stored data [3]. Likewise, 5G Security uses the NEA3-128 algorithm for privacy and the NIA3-128 algorithm for integrity. Both NEA3-128 and NIA3-128 are based on ZUC stream cipher [4]. However, many published researchers [5, 6] noticed that there are some weaknesses and vulnerabilities in the ZUC algorithm for differential power analysis attacks (SCA), Chosen IV attacks, etc. For this, we use chaos-based stream ciphers, which are very secure against cryptographic attacks because chaotic signals are intrinsically secure and have high nonlinearity [7]. The security of a stream cipher relies heavily on the pseudo-random number generator (PRNG), which acts as the primary component in the system. There has been a development of various cryptosystems in recent years that employ chaotic systems and maps, including those for the generation of pseudo-random numbers and encryption. Some of them have issues with security or poor computational performance [8; 9; 10; 11; 12; 13; 14; 15; 16]. Moreover, some of these cryptosystems are not well-suited for use on smart devices with limited resources, such as low memory, limited processing capabilities, and energy efficiency issues [17; 18; 19]. Devices used in the Internet of Things are low-power and resource constrained, so for these devices, hardware implementation of cryptosystems is more suitable than the software implementation. It is noteworthy that currently, there are only a limited number of chaotic systems that have been implemented on Field-Programmable Gate Array (FPGA) boards [20; 21; 22; 23; 24]. FPGAs are used for various reasons, including Speed (FPGAs can perform certain operations much faster than microprocessors), customizability, power efficiency, flexibility, and parallelism. A new lightweight chaos-based stream cipher, using two nonlinear feedback shift registers (NLFSR), was proposed by [PERSON] et al. [25] in 2019. The results obtained indicate the good cryptographic characteristics of their stream cipher. To provide security in multimedia applications dealing with high voluminous data, several effective chaos-based encryption systems using four combined chaotic maps (Logistic, Arnold, Lorenz, and Chebyshev) published by [PERSON] et al. [26] in 2020 and a novel medical image encryption system based on the Logistic-Tent map, Arnold's scrambling, and a special nonlinear function based LFSR was proposed by [PERSON] et al. [27] in 2021. Experimental works reveal that the proposed cryptosystems have good prospects for real-time image encryption. In 2022, [PERSON] et al. [28] developed a highly secure stream cipher based on the analog-digital hybrid chaotic system consisting of the Chen chaotic system and a modified three-dimensional Logistic map. The proposed stream cipher has the advantages of huge key space, virtually infinite cycle length, and tight security.