Secure Image Denoising over Two Clouds

Abstract

Multimedia processing with cloud is prevalent now, which the cloud server can provide abundant resources to processing various multimedia processing tasks. However, some privacy issues must be considered in cloud computing. For a secret image, the image content should be kept secret while conducting the multimedia processing in the cloud. Multimedia processing in the encrypted domain is essential to protect the privacy in cloud computing. Hu et al. proposed a novel framework to perform complex image processing algorithms in encrypted images with two cryptosystems: additive homomorphic encryption and privacy preserving transform. The additive homomorphic cryptosystem used in their scheme causes huge ciphertext expansion and greatly increases the cloud’s computation. In this paper, we modified their framework to a two-cloud scheme, and also implemented the random nonlocal means denoising algorithm. The complexity analysis and simulation results demonstrate that our new scheme is more efficient than Hu’s under the same denoising performance.