Efficient and Privacy-Preserving Outsourcing of 2D-DCT and 2D-IDCT

Abstract

As a subset of discrete Fourier transform (DFT), discrete cosine transform (DCT), especially two-dimensional discrete cosine transform (2D-DCT), is an important mathematical tool for digital signal processing. However, the computational complexity of 2D-DCT is quite high, which makes it impossible to meet the requirements in some signal processing fields with large signal sizes. In addition, to optimize the 2D-DCT algorithm itself, seeking help from a cloud platform is considered to be an excellent alternative to dramatically speeding up 2D-DCT operations. Still, there are three key challenges in cloud computing outsourcing that need to be addressed, including protecting the privacy of input and output data, ensuring the correctness of the returned results, and ensuring adequate local cost savings. In this paper, we explore the design of a practical outsourcing protocol for 2D-DCT and 2D-IDCT, which well solves the above three challenges. Both theoretical analysis and simulation experiment results not only confirm the feasibility of the proposed protocol but also show its outstanding performance in efficiency.