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Cloud-assisted image services are widely used for various applications. Dueto the high computational complexity of existing image encryption technology,it is extremely challenging to provide privacy preserving image services forresource-constrained smart device. In this paper, we propose a novelencrypressive cloud-assisted image service scheme, called eCIS. The key idea ofeCIS is to shift the high computational cost to the cloud allowing reduction incomplexity of encoder and decoder on resource-constrained device. This is donevia compressive sensing (CS) techniques, compared with existing approaches, weare able to achieve privacy protection at no additional transmission cost. Inparticular, we design an encryption matrix by taking care of image compressionand encryption simultaneously. Such that, the goal of our design is to minimizethe mutual information of original image and encrypted image. In addition tothe theoretical analysis that demonstrates the security properties andcomplexity of our system, we also conduct extensive experiment to evaluate itsperformance. The experiment results show that eCIS can effectively protectimage privacy and meet the user's adaptive secure demand. eCIS reduced thesystem overheads by up to $4.1\times\sim6.8\times$ compared with the existingCS based image processing approach.

Low-Complexity Cloud Image Privacy Protection via Matrix Perturbation