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With the evolution of technologies, the size of an image data has been significantly increased. However, traditional image encryption schemes cannot handle the emerging problems in big data such as noise toleration and compression. In order to meet today's challenges, we propose a new image encryption scheme based on chaotic maps and orthogonal matrices. The main core of the proposed scheme is based on the interesting properties of an orthogonal matrix. To obtain a random orthogonal matrix via the Gram Schmidt algorithm, a well-known nonlinear chaotic map is used in the proposed scheme to diffuse pixels values of a plaintext image. In the process of blockwise random permutation, the logistic map is employed followed by the diffusion process. The experimental results and security analyses such as key space, differential and statistical attacks show that the proposed scheme is secure enough and robust against channel noise and JPEG compression. In addition to complete encryption for higher security, it also supports partial encryption for faster processing as well.

Due to easy and simple implementation, normally single 1-D chaotic maps like logistic and sine maps are employed in multimedia data encryption. However, data encrypted through a single chaotic map does not provide better security in terms of resistance against various attacks. In this paper, 2D Henon chaotic map and skew tent map are deployed in the design of an efficient chaos-based image encryption algorithm. To confuse the relationship between plaintext and ciphertext images, both chaotic maps play a key role in the permutation and diffusion mechanism. In the confusion stage, firstly, the Henon chaotic map generates two different chaotic sequences, which are further applied in row and column permutation of plaintext image. The pixel values diffusion is produced by unimodal skew tent map via XOR operations. In the last stage of encryption algorithm, Hussain's substitution box is used to substitute each pixel into a new random pixel. Extensive security analysis and resistance to statistical attack prove the security of anticipated scheme.

Visual selective image encryption can both improve the efficiency of the image encryption algorithm and reduce the frequency and severity of attacks against data. In this article, a new form of encryption is proposed based on keys derived from Deoxyribonucleic Acid (DNA) and plaintext image. The proposed scheme results in chaotic visual selective encryption of image data. In order to make and ensure that this new scheme is robust and secure against various kinds of attacks, the initial conditions of the chaotic maps utilized are generated from a random DNA sequence as well as plaintext image via an SHA-512 hash function. To increase the key space, three different single dimension chaotic maps are used. In the proposed scheme, these maps introduce diffusion in a plain image by selecting a block that have greater correlation and then it is bitwise XORed with the random matrix. The other two chaotic maps break the correlation among adjacent pixels via confusion (row and column shuffling). Once the ciphertext image has been divided into the respective units of Most Significant Bits (MSBs) and Least Significant Bit (LSBs), the host image is passed through lifting wavelet transformation, which replaces the low-frequency blocks of the host image (i.e., HL and HH) with the aforementioned MSBs and LSBs of ciphertext. This produces a final visual selective encrypted image and all security measures proves the robustness of the proposed scheme.

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