Cross Border Data Flow Governance in Storage Cloud Leveraging Deep Learning Techniques

Abstract

Various federal laws (varying from country to country) govern geographically where a given category of data should reside, from where it should be accessible and where it should be restricted. Most of the data falling under the laws and regulation based on cross border data flow are unstructured data residing on file and object storage. Hence, it is vital for any unstructured data cloud storage system to cater to the requirements of cross border data flow compliance. The contribution of this paper is twofold which involves using deep learning models to categorize data residing on unified file and object storage as Personal Information and implementation of Geo-Fencing feature at the clustered file system level which helps regulate cross border data flow of the categorized Personal Information.