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Efficient verification of parallel matrix multiplication in public cloud: the MapReduce case
, Article Journal of Big Data ; Volume 7, Issue 1 , 2020 ; Amini, M ; Dolatnezhad Samarin, S ; Sharif University of Technology
Springer Science and Business Media Deutschland GmbH
2020
Abstract
With the advent of cloud-based parallel processing techniques, services such as MapReduce have been considered by many businesses and researchers for different applications of big data computation including matrix multiplication, which has drawn much attention in recent years. However, securing the computation result integrity in such systems is an important challenge, since public clouds can be vulnerable against the misbehavior of their owners (especially for economic purposes) and external attackers. In this paper, we propose an efficient approach using Merkle tree structure to verify the computation results of matrix multiplication in MapReduce systems while enduring an acceptable...