Abstract
The term “Big Data” is used to designate very large data sets, more varied and with more complex structures. Its characteristics are usually related to other challenges such as data storage, processing, analysis, or security. A Health Information System (HIS) refers to a system designed to manage healthcare data. This includes systems that collect, store, manage, and transmit data that is related to patients or the operational management of a hospital, clinic, testing laboratory, or any health care facility. Today, the health sector produces a significant amount of data. This information is voluminous and is stored in many different forms and types. It has become difficult to secure this data with traditional techniques and methods. The objective of this work is to propose a health data security process in a Big Data environment. The idea is to take advantage of the performance of Apache Hadoop and its components to create a secure environment for health data. The proposed solution will be based on four layers of security, the first component to be implemented in Apache Hadoop is Kerberos, the second element will be Apache Ranger, then Knox and finally we will use the encryption of Hadoop Distributed File System (HDFS).
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Ameskour, I., Benbrahim, H., Amine, A. (2023). Health Data Security in a Big Data Environment. In: Idrissi, N., Hair, A., Lazaar, M., Saadi, Y., Erritali, M., El Kafhali, S. (eds) Artificial Intelligence and Green Computing. ICAIGC 2023. Lecture Notes in Networks and Systems, vol 806. Springer, Cham. https://doi.org/10.1007/978-3-031-46584-0_17
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