Secret sharing approach for securing cloud-based pre-classification volume ray-casting

Abstract

With the evolution in cloud computing, cloud-based volume rendering, which outsources data rendering tasks to cloud datacenters, is attracting interest. Although this new rendering technique has many advantages, allowing third-party access to potentially sensitive volume data raises security and privacy concerns. In this paper, we address these concerns for cloud-based pre-classification volume ray-casting by using Shamir's (k, n) secret sharing and its variant (l, k, n) ramp secret sharing, which are homomorphic to addition and scalar multiplication operations, to hide color information of volume data/images in datacenters. To address the incompatibility issue of the modular prime operation used in secret sharing technique with the floating point operations of ray-casting, we consider excluding modular prime operation from secret sharing or converting the floating number operations of ray-casting to fixed point operations --- the earlier technique degrades security and the later degrades image quality. Both these techniques, however, result in significant data overhead. To lessen the overhead at the cost of high security, we propose a modified ramp secret sharing scheme that uses the three color components in one secret sharing polynomial and replaces the shares in floating point with smaller integers.