Security model for Big Healthcare Data Lifecycle

Big data is a concept that aimed at collecting, storing, processing and transforming large amount of data into value using new combination of strategies and technologies. Big data is characterized by data that have a large volume, massive velocity, numerous variety, useful value, and veracity. Big Data Analytics offers tremendous insights to different organizations especially in healthcare. Currently, Big healthcare data has the highest potential for improving patient outcomes, gaining valuable insights, predicting outbreaks of epidemics, avoiding preventable diseases and effectively minimizing the cost of healthcare delivery. However, the dynamic nature of health data presents various conceptual, technical, legal and ethical challenges associated with the data processing and analysis activities. The big data security and privacy concepts are some of the most pertinent issues and have become increasingly significant associated with big healthcare data in the modern world. In this paper, we give an overview of big data characteristics and challenges in healthcare and present big healthcare data lifecycle integrated with security threats and attacks to provide encompass policies and mechanisms that aim at solving the various security challenges in each step of big data lifecycle. The focus is also placed on the description of the recently proposed techniques related to authentication, encryption, anonymization, access control, and privacy. We finally propose an approach to secure threat model for big healthcare data lifecycle as a main contribution of this paper. (C) 2018 The Authors. Published by Elsevier Ltd.