A Randomized Kernel-Based Secret Image Sharing Scheme

TL;DR

This paper introduces a flexible ($k,n$)-threshold secret image sharing scheme using a randomized kernel, optimizing security and storage efficiency, and eliminating single points of failure.

Contribution

It presents a novel randomized kernel-based scheme that balances security, storage, and computational efficiency for secret image sharing.

Findings

Shares are smaller or equal in size to the secret image.

Kernel optimization enhances security and computational performance.

The scheme is free from single point of failure.

Abstract

This paper proposes a ($k,n$)-threshold secret image sharing scheme that offers flexibility in terms of meeting contrasting demands such as information security and storage efficiency with the help of a randomized kernel (binary matrix) operation. A secret image is split into $n$ shares such that any $k$ or more shares ($k\leq n$) can be used to reconstruct the image. Each share has a size less than or at most equal to the size of the secret image. Security and share sizes are solely determined by the kernel of the scheme. The kernel operation is optimized in terms of the security and computational requirements. The storage overhead of the kernel can further be made independent of its size by efficiently storing it as a sparse matrix. Moreover, the scheme is free from any kind of single point of failure (SPOF).