Remote sensing image and multi-type image joint encryption based on NCCS

Abstract

In this paper, an algorithm based on the novel Chebyshev chaotic system (NCCS) for remote sensing image encryption and joint encryption of remote sensing images, grayscale images and color images is proposed. In view of the large amount of remote sensing image data, this paper proposes NCCS, which effectively reduces the time complexity of the algorithm and produces a more uniform pseudo-random sequence with better performance. On this basis, the remote sensing image is encrypted, first put each band of the remote sensing image into different channels, to obtain a three-dimensional matrix, the use of 3-D spiral curve to read each side of the three-dimensional matrix one by one, the obtained one-dimensional sequence into the two-dimensional matrix, this method makes each channel produce a certain coupling at the same time also reduces the dimension of the matrix, effectively enhance the effect of chaos. The chaos map is used to scramble the one-dimensional sequences once, and then to scramble between these one-dimensional sequences, and the method of circular left shift is used to diffuse. Because this method is suitable for encryption of images with multiple channels, it can be used not only for remote sensing image encryption, but also for joint encryption of remote sensing, grayscale, and color images. Simulation results and performance analysis show that the proposed method has good safety. Compared to some existing encryption schemes, this method is more widely applicable.

A Universal Image Compression Sensing-Encryption Algorithm Based on DNA-Triploid Mutation

“…Test results in Table 4 show that both values are close to theoretical expectations of NPCR and UACI which indicate that a certain ability to resist differential attacks is provided by this algorithm. It is presented in Table 5 for a comparison with other algorithms for both NPCR and UACI [38][39][40][41]. Algorithm NPCR (%) UACI (%) Reference [38] 99.6049 99.4838 Reference [39] 99.6089 99.4374 Reference [40] 99.5900 33.4467 Reference [41] 99.6100 33.4500 Proposed 99.6120 33.5166 Theoretical value 99.6094 33.4635…”

“…It is presented in Table 5 for a comparison with other algorithms for both NPCR and UACI [38][39][40][41]. Algorithm NPCR (%) UACI (%) Reference [38] 99.6049 99.4838 Reference [39] 99.6089 99.4374 Reference [40] 99.5900 33.4467 Reference [41] 99.6100 33.4500 Proposed 99.6120 33.5166 Theoretical value 99.6094 33.4635…”

A Novel Remote Sensing Image Encryption Scheme Based on Block Period Arnold Scrambling

“…With the rapid development of the information technology, the information sharing brings convenience to people. People pay more attention to the protection of the key information in the sharing process [1]. Some recent studies show that the traditional encryption algorithms may be difficult to meet the high confidentiality requirements when the computer processes the satellite remote sensing image data.…”

“…Qin et al use the new pixel coordinates obtained from the chaotic matrix information to perform the displacement and diffusion operations [21]. Liu et al use the chaotic sequences generated by the NCCS to randomize the one-dimensional matrix images [22]. The remote sensing images are encrypted by the classical diffusion method of cyclic left-side modetaking and mode-adding.…”