Repository logo
 

safest: a safeguarding analytical framework for decentralised sensitive data

Published version
Peer-reviewed

Type

Article

Change log

Authors

Ryser-Welch, Patricia 
Abarrantegui, Leire 

Abstract

An increasing demand and dependence of analyzing a data has been driven by “big data” and “Internet of Things (IoT)”. Scientific reproducibility, robustness and the cost of capturing new data has been improved through findable, accessible, interoperable, and reusable data sharing. Ethical and legal restrictions impose the use of privacy preservation and protection measures for any disclosure and sensitive information. We, therefore, present a possible model to support multi-disciplinary research team to protect against disclosure of individual-level data and large datasets used in other disciplines. We argue technology reliance is not enough and a continuous collaboration that adapt to new cyber-security, and data inferential threat is needed. We consequently conclude some standards could lead to closer collaboration to support research and innovation in the long term.

Description

Keywords

Journal Title

International Journal of Advancements in Technology

Conference Name

Journal ISSN

0976-4860
0976-4860

Volume Title

Publisher

IJoAT Foundation

Publisher DOI