Compression and encryption for remote sensing image using chaotic system

Wong

et al. 2016

IEEE Trans. Multimedia

Some pioneering works have investigated embedding cryptographic properties in compressive sampling (CS) in a way similar to one-time pad symmetric cipher. This paper tackles the problem of constructing a CS-based symmetric cipher under the key reuse circumstance, i.e., the cipher is resistant to common attacks even a fixed measurement matrix is used multiple times. To this end, we suggest a bi-level protected CS (BLP-CS) model which makes use of the advantage of the non-RIP measurement matrix construction. Specifically, two kinds of artificial basis mismatch techniques are investigated to construct key-related sparsifying bases. It is demonstrated that the encoding process of BLP-CS is simply a random linear projection, which is the same as the basic CS model. However, decoding the linear measurements requires knowledge of both the key-dependent sensing matrix and its sparsifying basis. The proposed model is exemplified by sampling images as a joint data acquisition and protection layer for resource-limited wireless sensors. Simulation results and numerical analyses have justified that the new model can be applied in circumstances where the measurement matrix can be re-used.Comment: 14 pages, 8 figure

“…I. Scrambling is performed on the measurements, such as [20], [21]; II. Scrambling is done in the frequency domain, such as [22], [25].…”

Section: B Scrambling In the Measurements Domain Or The Frequency Domentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Bi-level Protected Compressive Sampling

Wong

et al. 2016

IEEE Trans. Multimedia

“…Arnold's cat map is invertible [10,11,13]. This is important, because it allows the image to be retrieved during the decryption process.…”

Section: Introductionmentioning

confidence: 99%

Colored image encryption and decryption using multi-chaos 2D quadratic strange attractors and matrix transformations

Alsaedi

2016

Multimed Tools Appl

Data security is an increasingly important issue. In this paper, a scheme to encrypt and decrypt colored images is presented in which two random secret keywords are used as parameters for quadratic maps with strange attractors. The scheme uses the well-known chaotic trait of sensitivity to initial conditions to ensure that the receiver generates the same sequences. After forming the quadratic maps and zeros removal from both maps, three codebooks are formed one from the original image and two from the two images of the quadratic maps. The input colored image is decomposed into three components and quantized using two of the three codebooks. The resulting image is subjected to partial extended Arnold's transform then to Gould transformation to hide image traces. The partial extended Arnold's matrix which is subjected to a determinant condition is studied for possible number of rotations for specific sizes of sub-blocks taken from a random image and then the results are used for encryption and decryption of different colored images. Then, the pixels of the components are shifted cyclically with a predefined number of shifts and quantized using the third codebook with maximum MSE. The results from the statistical analysis show that the pixels correlation is very low and the ciphered image is well shuffled. Also, the decrypted images have high PSNR at the receiver. Furthermore, compariosns with other schemes in the literature show that the performance of the proposed algorithm is high.

“…An image encryption algorithm was proposed by combining the DCT with 2D chaotic map to solve the problem of poor security and small key space in one-dimensional chaotic cryptosystems [31]. In 2015, an image compression and encryption algorithm was devised, in which the chaotic system was employed to generate pseudo-random measurement matrices [32]. To further improve the security and the compression performance of image encryption schemes, TONG et al presented a color image compression and encryption scheme based on the hyper-chaotic system, where the dictionary of discrete cosine transform was exploited to represent the color image sparsely [33].…”

Section: Introductionmentioning

confidence: 99%

Image compression and encryption algorithm based on advanced encryption standard and hyper-chaotic system

Nie¹,

Liu²,

He³

et al. 2019

Optica Applicata

An image compression and encryption algorithm by combining the advanced encryption standard (AES) with the hyper-chaotic system is designed, in which Arnold map is employed to eliminate part of the block effect in the image compression process. The original image is compressed with the assistance of a discrete cosine transform and then its transform coefficients are encrypted with the AES algorithm. Besides, the hyper-chaotic system is adopted to introduce the nonlinear process for image encryption. Numerical simulations and theoretical analyses demonstrate that the proposed image compression and encryption algorithm is of high security and good compression performance.