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A Weighted Threshold Secret Sharing Scheme for Remote Sensing Images Based on Chinese Remainder Theorem
Shanghai Ocean University, Shanghai, 201306, China.
Deakin University, 221 Burwood HWY, Burwood, VIC 3125, Australia .
Shanghai Jian Qiao University, Shanghai, 201306, China.
Yanshan University, Hebei, 066004, China.
Electric Power University, Shanghai, 200090, China.
Donghua University, Shanghai, 200051, China.
* Corresponding Author: Huifang Xu. Email: .
Computers, Materials & Continua 2019, 58(2), 349-361. https://doi.org/10.32604/cmc.2019.03703
Abstract
The recent advances in remote sensing and computer techniques give birth to the explosive growth of remote sensing images. The emergence of cloud storage has brought new opportunities for storage and management of massive remote sensing images with its large storage space, cost savings. However, the openness of cloud brings challenges for image data security. In this paper, we propose a weighted image sharing scheme to ensure the security of remote sensing in cloud environment, which takes the weights of participants (i.e., cloud service providers) into consideration. An extended Mignotte sequence is constructed according to the weights of participants, and we can generate image shadow shares based on the hash value which can be obtained from gray value of remote sensing images. Then we store the shadows in every cloud service provider, respectively. At last, we restore the remote sensing image based on the Chinese Remainder Theorem. Experimental results show the proposed scheme can effectively realize the secure storage of remote sensing images in the cloud. The experiment also shows that no matter weight values, each service providers only needs to save one share, which simplifies the management and usage, it also reduces the transmission of secret information, strengthens the security and practicality of this scheme.Keywords
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