A Multi-Layer Big Data Value Chain Approach for Security Issues
Abou Zakaria Faroukhi, Imane El Alaoui, Youssef Gahi, Aouatif Amine · Procedia Computer Science · 2020
Big Data systems generate a lot of data from different sources, sometimes are less reliable. Also, business ecosystems are highly interconnected, through Big Data Value Chains (BDVC) either internally or with partners, making their data assets and processes more vulnerable to multiple cyber-attacks. However, this kind of sensitive exposition and data workflows requires specific protection and security management. In this contribution, we highlight the importance of coupling BDVC and Big Data security as well as existing contributions addressing these topics. Also, we propose a multi-dimensional model aiming to show cybersecurity milestones and reduce the gap between cyber-risks and how organizations manage their data. For this goal, we suggest a multi-layered security framework to deal with security issues along BDVC. This framework, which is a generic view adaptable to different domains, allows protecting organizations’ sensitive data assets as well as privacy concerns. Furthermore, this multi-layer projection ensures a sustainable cyber-ecosystem.