# Image Encryption Algorithms: A Survey of Design and Evaluation Metrics
## 2 Image Encryption Algorithms
### Meaningful Encryption  
Meaningful image encryption is a technique that utilizes image encryption and steganography to produce cipher images that have a visually meaningful image instead of a noise-like image. Steganography is the practice of concealing data within another non-secret carrier file or message to avoid detection. There are two steps in a meaningful encryption algorithm. First, the image is encrypted using an image encryption algorithm. Next, the resulting encrypted image is embedded in a non-secret carrier image using a steganography algorithm. The carrier image, which looks like a normal image, can then be transmitted to the receiver. [PERSON] et al. [46] proposed an image encryption algorithm, utilizing compressive sensing, chaotic maps, and steganography to produce meaningful cipher images. The proposed algorithm consists of two stages: a compressive sensing encryption step and a steganography step. For the compressive sensing encryption step, a 2D logistic-adjusted sine map (2D-LASM) and a 3D cat map are generated from a secret key. Then, the plaintext image is transformed into a sparse domain using DWT and permuted using the chaotic sequence generated by the 2D-LASM. The measurement matrix for compressive sensing is constructed using the chaotic sequences generated by the 3D cat map and the 2D-LASM. Finally, the measurement matrix is used to compress and encrypt the permuted image. In the steganography step, the resulting cipher image is embedded into a carrier image, and the order of the embedding position is encrypted using the chaotic sequence generated by the 2D-LASM. In [47], [PERSON] et al. proposed a meaningful image encryption based on a chaotic map and random scrambling diffusion. The plaintext is first sparsified by wavelet packet transform (WPT). Next, a one-dimensional chaotic map is used to construct the measurement and permutation matrices. Then, a bidirectional random scrambling algorithm based on chaotic magic transformation (CMT) is used to permute the sparsified plaintext image. The permuted resulting image is compressed using the chaotic measurement matrix and then diffused using chaotic pixel diffusion. Finally, the encrypted and compressed image is embedded in a carrier image using the WPT embedding algorithm. [PERSON] et al. [48] proposed a novel meaningful image encryption algorithm based on parallel compressive sensing and slant transform. First, the plaintext image is sparsified by DWT and the sparse coefficient matrix of the plaintext image is used as the control parameters for the 4D memristive hyperchaotic map, which generates the scrambling matrix. Then, the sparsified plaintext image is permuted and compressed using Arnold scrambling and parallel compressive sensing to produce the cipher image. Finally, the cipher image is randomly embedded in a carrier image by slant transform-based embedding in a block-wise manner to produce a visually meaningful cipher image. In [49], [PERSON] et al. proposed a visually meaningful image encryption algorithm based on a new universal embedding model (UEM). The new UEM is used to embed secret information into the host and to adapt to different types of wavelet transforms. First, the plaintext image is encrypted using an image encryption algorithm (the authors did not specify an exact algorithm) to produce a permuted and diffused image. Next, integer wavelet transform is performed on the carrier image to obtain the wavelet transform domain. Then, a four-dimensional discrete chaotic system is used to embed the permuted and diffused image in the integer wavelet sub-bands of the carrier image. Finally, inverse integer wavelet transform (iIWT) is performed on the resulting wavelet transform domain to produce a visually meaningful cipher image. Meaningful image encryption algorithms have the advantage of keeping the embedded data secure even if the embedded image data are extracted via steganalysis tools.