A Data Minimization Algorithm for Fast and Secure Transfer of Big Datasets Using Fourier Analysis

Abstract

Today’s increased demand for fast and secure transfer of big data applications and files has motivated researchers to develop novel algorithms within the framework of existing protocol limitations. Transferring big data datasets (e.g. Big Genomic Datasets) over the network has always been an interesting and challenging research area. This is because all data transfer protocols, such as HTTP and FTP, use the standard content-encoding schemes, namely ASCII, which offer little or no compression or data minimization. The purpose of this work is to design and implement a novel Fourier-based data minimization algorithm to decrease the required time to transfer multi-dimensional big datasets over conventional networks. In addition, we increased security in the event of a data breach. Moreover, it will introduce a generic concept that can be used by cloud-based applications to secure data that is being exchanged remotely. One and two-dimensional results show how the method could effectively be used in different data minimization scenarios.