## 3 Related Works  
Lizard is a lightweight stream cipher introduced by [6]. Lizard is designed for use with power-constrained devices such as passive RFID tags. The hardware efficiency is the consequence of merging a Grain-like design with the FP (1)-mode, a newly proposed building concept for the state initialisation of stream ciphers. Lizard employs 120-bit keys, 64-bit IVs, and a 121-bit inner state length as part of its core processes. As a result, Lizard can generate up to 218 keystream bits per key/IV pair, which makes it suitable with currently used communication protocols, such as Bluetooth, WLAN and HTTPS. The results show that Lizard's hardware design is more efficient than other hardware-based ciphers. In addition, Lizard is suitable for applications that do not require high-speed encryption rates. In [24], the researchers presented a new lightweight RFID-based authentication solution that employs a stream cipher to ensure privacy between valid components. The suggested method eliminates the inherent linearity of LFSRs by using a variety of keystream generators such as And2 LFSR, Geffe and majority-based. This allows for the construction of a nonlinear pseudorandom number generator (PRNG). For statistical analysis, the authors employed a multiple polynomial quadratic sieve. The simulation results show that the proposed authentication technique's performance is affected by the kind of error control code, nonlinear combinational functions and the degree of the generator polynomial. The researchers in [25] developed a new deep learning-based key generation network called DeepKeyGen that acts as a stream cipher generator to produce the secret key for medical image encryption. DeepKeyGen's main goal is to learn the mapping relationship that describes how to convert a given image into a secret key. Security analysis demonstrates that the keystream generated by DeepKeyGen is highly sensitive to change, possesses a large key space, is pseudorandom, and is resistant to a variety of attacks. Statistically, only entropy tests are applied. Further statistical and performance analysis is needed to ensure the algorithm's efficiency. \begin{table}
\begin{tabular}{c c c} \hline \hline
**Mean (\(I_{\mu}\))** & **Stand. Dev. (\(I_{\sigma}\))** & **Stoke Type** \\ \hline
61.1 & 0.576 & \(-\)stroke (less than 20 kA) \\
33.3 & 0.263 & \(-\)stroke (greater than 20 kA) \\
33.9 & 0.527 & \(+\)stroke \\ \hline \hline \end{tabular}
\end{table} 
Table 1: Logarithmic normal distribution of lightning current parameters [23]. Figure 2: Lightning strike development through time \(t\). Another stream cipher for image encryption is presented in [26]. The stream cipher is designed to ensure the safe transmission of images between different parties. As part of the pixel manipulation process, a combination of two-dimensional discrete wavelet transforms and the Arnold mapping algorithm are used. The experimental results demonstrate that the proposed stream cipher is secure in terms of randomness and statistics. However, the work does not provide sufficient detail about the performance of the cipher in terms of speed and throughput. In [27], an image encryption cipher based on fixed-point chaotic maps is proposed. The correlation coefficient, differential attack, histogram and information entropy are some of the security analyses that are used in the process of evaluating the algorithm. Statistically, correlation coefficient analysis is performed, and the tests demonstrate resistance to entropy attacks. However, the algorithm's throughput is low (186.84 Mb/s) compared to other existing secure stream ciphers. In addition, other statistical tests are needed (e.g., NIST tests) to ensure its resistance to statistical attacks. A stream cipher based on adding offsets to the two-dimensional coupled map lattice (2D-CML) is developed in [28]. The technique proposes adding distinct offsets to each lattice. The offset 2D CML model outperforms the original 2D-CML model in terms of its chaotic qualities; specifically, it has larger Lyapunov exponents (LE).