A novel multi‐image visually meaningful encryption algorithm based on compressive sensing and Schur decomposition

The digital image, as the critical component of information transmission and storage, has been widely used in the fields of big data, cloud and frog computing, Internet of things, and so on. Due to large amounts of private information in the digital image, the image protection is fairly essential, and the designing of the encryption image scheme has become a hot issue in recent years. In this paper, to resolve the shortcoming that the probability density distribution (PDD) of the chaotic sequences generated in the original two-dimensional coupled map lattice (2D CML) model is uneven, we firstly proposed an improved 2D CML model according to adding the offsets for each node after every iteration of the original model, which possesses much better chaotic performance than the original one, and also its chaotic sequences become uniform. Based on the improved 2D CML model, we designed a compressive image encryption scheme. Under the condition of different keys, the uniform chaotic sequences generated by the improved 2D CML model are utilized for compressing, confusing, and diffusing, respectively. Meanwhile, the message authentication code (MAC) is employed for guaranteeing that the encryption image be integration. Finally, theoretical analysis and simulation tests both demonstrate that the proposed image encryption scheme owns outstanding statistical, well encryption performance, and high security. It has great potential for ensuring the digital image security in application.

Section: Introductionmentioning

confidence: 99%

A Novel Compressive Image Encryption with an Improved 2D Coupled Map Lattice Model

Liu

Wang

Zhang

et al. 2021

“…Image encryption is usually pursued in the frequency and spatial domains. Reference [16] used frequency domain encryption, wherein the plain image was first transformed with the discrete wavelet transform and then compressed. e carrier image was then processed by lifting the wavelet transform and discrete cosine transform together with a Schur decomposition.…”

Section: Introductionmentioning

confidence: 99%

Self-Adaptive Image Encryption Algorithm Based on Quantum Logistic Map

Dong

Huang

Mei

et al. 2021

Self Cite

This study proposes a self-adaptive image encryption algorithm based on the quantum logistic map. First, the initial values are substituted into the quantum logistic map based on an iteration process to generate three random sequences. After preprocessing, three new random sequences with better randomicity were obtained from the generated random sequences. In particular, the correlation coefficients for random sequences before and after preprocessing are compared to determine the best model to make the correlation coefficients closer to zero. Second, one random sequence in the scrambling stage is selected with respect to the plain image. The selected random sequence is then used to perform row-column perturbation on the plain image. Finally, the remaining two random sequences are used to perform forward and reverse diffusion to obtain the final cipher image. Because of the dependence on the plain image, the algorithm can frustrate the chosen-plaintext and known-plaintext attacks. Experimental results show that the proposed encryption algorithm can achieve secure communications.

“…Visible watermarking technology has important applications in many fields, such as content protection [1,2], copyright identification [3], document security [4,5], and advertising [6]. In the past two decades, there have been a large number of algorithms with different features in visible watermarking technology.…”

Section: Introductionmentioning

confidence: 99%

An Adaptive Visible Watermark Embedding Method based on Region Selection

Liu

Guo

et al. 2021

Aiming at the problem that the robustness, visibility, and transparency of the existing visible watermarking technologies are difficult to achieve a balance, this paper proposes an adaptive embedding method for visible watermarking. Firstly, the salient region of the host image is detected based on superpixel detection. Secondly, the flat region with relatively low complexity is selected as the embedding region in the nonsalient region of the host image. Then, the watermarking strength is adaptively calculated by considering the gray distribution and image texture complexity of the embedding region. Finally, the visible watermark image is adaptively embedded into the host image with slight adjustment by just noticeable difference (JND) coefficient. The experimental results show that our proposed method improves the robustness of visible watermarking technology and greatly reduces the risk of malicious removal of visible watermark image. Meanwhile, a good balance between the visibility and transparency of the visible watermark image is achieved, which has the advantages of high security and ideal visual effect.