A Weighted Threshold Secret Sharing Scheme for Remote Sensing Images Based on Chinese Remainder Theorem

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.

Proactive Weighted Threshold Signature Based on Generalized Chinese Remainder Theorem

This paper proposes a new proactive weighted threshold signature scheme based on Iflene＇s general secret sharing, the generalized Chinese remainder theorem, and the RSA threshold signature, which is itself based on the Chinese reminder theorem. In our scheme, group members are divided into different subgroups, and a positive weight is associated to each subgroup, where all members of the same subgroup have the same weight. The group signature can be generated if and only if the sum of the weights of members involved is greater than or equal to a fixed threshold value. Meanwhile, the private key of the group members and the public key of the group can be updated periodically by performing a simple operation aimed at refreshing the group signature message. This periodical refreshed individual signature message can enhance the security of the proposed weighted threshold signature scheme.

Iteratively weighted thresholding homotopy method for the sparse solution of underdetermined linear equations

Recently, iteratively reweighted methods have attracted much interest in compressed sensing, outperforming their unweighted counterparts in most cases. In these methods, decision variables and weights are optimized alternatingly, or decision variables are optimized under heuristically chosen weights. In this paper,we present a novel weighted l1-norm minimization problem for the sparsest solution of underdetermined linear equations. We propose an iteratively weighted thresholding method for this problem, wherein decision variables and weights are optimized simultaneously. Furthermore, we prove that the iteration process will converge eventually. Using the homotopy technique, we enhance the performance of the iteratively weighted thresholding method. Finally, extensive computational experiments show that our method performs better in terms of both running time and recovery accuracy compared with some state-of-the-art methods.