| Title | A Platform for Private and Controlled Spreadsheet Objects Sharing |
| Publication Type | Conference Paper |
| Year of Publication | 2019 |
| Authors | Camera, Giancarlo, Baglietto, Pierpaolo, Maresca, Massimo |
| Conference Name | 2019 IEEE 23rd International Enterprise Distributed Object Computing Conference (EDOC) |
| Keywords | authorisation, business data processing, collaborative analytics, collaborative editing, Computer supported collaborative work, confidential data exchange, cryptography, Data analysis, data integrity, data privacy, data storage, Data visualization, groupware, office automation, privacy, Protocols, pubcrawl, resilience, Resiliency, Secure File Sharing, Secure spreadsheet data sharing, sensitive data sharing, spreadsheet file sharing, spreadsheet objects sharing, Spreadsheet programs, Spreadsheets, spreadsheets collaborative authoring applications, storage management, tabular data |
| Abstract | Spreadsheets are widely used in industries for tabular data analysis, visualization and storage. Users often exchange spreadsheets' semi-structured data to collaborative analyze them. Recently, office suites integrated a software module that enables collaborative authoring of office files, including spreadsheets, to facilitate the sharing process. Typically spreadsheets collaborative authoring applications, like Google Sheets or Excel online, need to delocalize the entire file in public cloud storage servers. This choice is not secure for enterprise use because it exposes shared content to the risk of third party access. Moreover, available platforms usually provide coarse grained spreadsheet file sharing, where collaborators have access to all data stored inside a workbook and to all the spreadsheets' formulas used to manipulate those data. This approach limits users' possibilities to disclose only a small portion of tabular data and integrate data coming from different sources (spreadsheets or software platforms). For these reasons enterprise users prefer to control fine grained confidential data exchange and their updates manually through copy, paste, attach-to-email, extract-from-email operations. However unsupervised data sharing and circulation often leads to errors or, at the very least, to inconsistencies, data losses, and proliferation of multiple copies. We propose a model that gives business users a different level of spreadsheet data sharing control, privacy and management. Our approach enables collaborative analytics of tabular data focusing on fine grained spreadsheet data sharing instead of coarse grained file sharing. This solution works with a platform that implements an end to end encrypted protocol for sensitive data sharing that prevents third party access to confidential content. Data are never shared into public clouds but they are transferred encrypted among the administrative domains of collaborators. In this paper we describe the model and the implemented system that enable our solution. We focus on two enterprise use cases we implemented describing how we deployed our platform to speed up and optimize industry processes that involve spreadsheet usage. |
| DOI | 10.1109/EDOC.2019.00018 |
| Citation Key | camera_platform_2019 |
A Platform for Private and Controlled Spreadsheet Objects Sharing