Data Reconstruction Through Sequence Based Mapping in Secured Data Partitioning

Abstract

Recent researches have proposed data partitioning technique with secret sharing to enhance the security in cloud computing. However, its complexity in reconstructing while preserving confidentiality has a limitation of practical use, specifically when it involves a large amount of data. In this paper, we explored the existing mapping technique called partition based indexing that is being used to reconstruct the shares. Nevertheless, we found that its efficiency has decreased when the amount of data increased. Thus, this has motivated us to propose a sequence based mapping to increase the efficiency of data reconstruction in secured data partitioning with secret sharing. The proposed technique has been evaluated through a series of simulation using 10000 data. The performance was evaluated based on the time taken to achieve data reconstruction for different number of shares. As a result, we proved that our proposal, which is named as a sequence based mapping technique has successfully improved more than 40 percent of the performance of data reconstruction compared to indexing technique. As such, we conclude that our proposal on sequence based mapping is an ideal technique for improving performance of data reconstruction in data-partitioning with secret sharing and preserving confidentiality of big data in cloud computing.