Privacy preserving, verifiable and efficient outsourcing algorithm for matrix multiplication to a malicious cloud server. Issue 1 (1st January 2017) - Kumar, Malay; Meena, Jasraj; Vardhan, Manu
Abstract: Matrix Multiplication is a basic engineering and scientific problem, which has application in various domains. There exists many cryptographic solutions for secure computation of matrix multiplication, but cryptographic preamble makes them infeasible for outsourcing with large input size to the cloud server. In this paper, we propose a privacy-preserving, verifiable and efficient algorithm for matrix multiplication in outsourcing paradigm illustrated by the following scenario: the client is having a large data-set and needs to perform matrix multiplication, but unable to process due to the lack of computing resources. Therefore, the client outsources the computation to the cloud server. We evaluate the algorithm on security, efficiency and verifiability parameters and discuss the implementation details. The result analysis shows that the algorithm is highly efficient and endorses the practical usability of the algorithm. Using this algorithm, we can mostly replace the costly cryptographic operations and securely solve matrix multiplication on a large data-set.