# A Dynamic Multi-Layer Steganography Approach Based on Arabic Letters' Diacritics and Image Layers
## 2 Related Work
### Image Steganography Methods  
Based on literature studies in steganography, two basic ways to embed sensitive data in images exist. The first is spatial domain methods, and the second is the transform domain technique [8]. The first method relies on a direct change in some of the bits in the image without causing noticeable modifications to the image's appearance. For this, the binary-encoded secret is embedded into the least significant bit [9; 10]. The researchers in [11] used the genetic algorithm to find the most suitable places for hiding. [PERSON] et al. used all RGB color image bits for embedding [12]. Furthermore, the authors of [10; 13] used edge technology in the images to embed secrets. The second method of image-based steganography relies on changing the features of the secret before hiding it in the picture to increase security and complicate the detection process. For example, with encryption, the original information cannot be fully recovered if the secret hidden in the image is not found. On the other  
\begin{table}
\begin{tabular}{c c c c} \hline \hline \(\downarrow\) & \(\downarrow\)\(\downarrow\)\(\uparrow\) & \(\downarrow\)\(\downarrow\)\(\downarrow\)\(\downarrow\) & \(\downarrow\)\(\downarrow\)\(\downarrow  
hand, to raise the level of security, other methods adopted inserting bits in a different order from the natural sequence of pixels, such as inserting a pixel that achieves a significant difference from the adjacent pixel so that it does not exceed a certain threshold [14; 15]. Some approaches also used special encodings and did not rely on standard encodings to increase the level of confidentiality [16], whereas others compressed the data before encoding it to increase the size of the message that can be hidden [17]. Furthermore, when working with images, there are many options to increase the level of complexity, such as embedding in the gray level or within the color layers in a certain agreed order [18; 19], or in the histogram instead of the basic image [20]. Moreover, [21] utilized double-cover steganography by applying two covers in the concealment process to increase the security of secret information. In 2016, [PERSON] and [PERSON] introduced a steganography technique based on the discrete wavelet transform (DWT) to minimize distortion in the cover image. However, this method involves a trade-off between security and imperceptibility, prioritizing higher security over imperceptibility [22]. In 2018, [PERSON] et al. proposed a DWT-based steganography approach that employed three different coefficients--horizontal, vertical, and diagonal--to conceal confidential images. They also presented a secret key technique to mitigate visual quality distortion in the stego-image [23]. [PERSON] et al. (2017) discussed an intriguing method for audio steganography to improve payload capacity, security, and robustness by utilizing two levels of integer wavelet transform and modifying wavelet and chaotic map coefficients. However, this scheme achieved a hiding capacity of 25% of the cover image and an SNR of 44.6 dB [24]. In 2018, [PERSON] et al. proposed an image steganography technique based on fuzzy wavelet and DWT, which they tested by embedding text within an image [25]. Finally, in 2019, [PERSON] et al. proposed a CNN-MLP-based classifier for image classification, combining the positive features of a convolutional neural network (CNN) and multilayer perceptron (MLP) to enhance image detection capabilities [26]. In 2022, [PERSON] et al. proposed an algorithm that introduces a robust and blind color image steganography method using fractal cover images, SVD, IWT, and DWT. This algorithm achieves high security, imperceptibility, and a large hiding capacity. Performance analysis shows minimal image degradation and efficient resource utilization [27]. In conclusion, the proposed image steganography algorithm presents a novel approach using fractal images as cover images.